Analysis of 111/999 NHS calls and 111 online reports
Quentin Leclerc, Emily Nightingale, Samuel Abbott & Thibaut Jombart, for CMMID
Saturday 06 February 2021
1 Data preparation
1.1 Outline
Load scripts: loads libraries and useful scripts used in the analyses; all
.Rfiles contained inscriptsat the root of the factory are automatically loadedLoad data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.
1.2 Load packages
library(reportfactory)
library(here)
library(rio)
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)1.3 Load scripts
These scripts will load:
- all scripts stored as
.Rfiles inside/scripts/ - all scripts stored as
.Rfiles inside/src/
These scripts also contain routines to access the latest clean encrypted data (see next section).
1.4 Load clean data
We import the latest NHS pathways data:
x <- import_pathways() %>%
as_tibble()
x
## [90m# A tibble: 428,473 x 11[39m
## site_type date sex age ccg_code ccg_name count postcode nhs_region
## [3m[90m<chr>[39m[23m [3m[90m<date>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<int>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m
## [90m 1[39m 111 2020-03-18 fema… miss… e380000… nhs_glo… 1 gl34fe South West
## [90m 2[39m 111 2020-03-18 fema… miss… e380001… nhs_sou… 1 ne325nn North Eas…
## [90m 3[39m 111 2020-03-18 fema… 0-18 e380000… nhs_air… 8 bd57jr North Eas…
## [90m 4[39m 111 2020-03-18 fema… 0-18 e380000… nhs_ash… 7 tn254ab South East
## [90m 5[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 35 rm13ae London
## [90m 6[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 9 n111np London
## [90m 7[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 11 s752py North Eas…
## [90m 8[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bas… 19 ss143hg East of E…
## [90m 9[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bas… 6 dn227xf North Eas…
## [90m10[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bat… 9 ba25rp South West
## [90m# … with 428,463 more rows, and 2 more variables: day [3m[90m<int>[90m[23m, weekday [3m[90m<fct>[90m[23m[39mWe also import demographics data for NHS regions in England, used later in our analysis:
path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
## nhs_region variable value
## 1 North West 0-18 0.22538599
## 2 North East and Yorkshire 0-18 0.21876449
## 3 Midlands 0-18 0.22564656
## 4 East of England 0-18 0.22810783
## 5 London 0-18 0.23764782
## 6 South East 0-18 0.22458811
## 7 South West 0-18 0.20799797
## 8 North West 19-69 0.64274078
## 9 North East and Yorkshire 19-69 0.64437753
## 10 Midlands 19-69 0.63876675
## 11 East of England 19-69 0.63034229
## 12 London 19-69 0.67820084
## 13 South East 19-69 0.63267336
## 14 South West 19-69 0.63176131
## 15 North West 70-120 0.13187323
## 16 North East and Yorkshire 70-120 0.13685797
## 17 Midlands 70-120 0.13558669
## 18 East of England 70-120 0.14154988
## 19 London 70-120 0.08415135
## 20 South East 70-120 0.14273853
## 21 South West 70-120 0.16024072Finally, we import publically available deaths per NHS region:
dth <- import_deaths() %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
#truncation to account for reporting delay
delay_max <- 21
dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
## date_report nhs_region deaths
## 1 2020-03-01 East of England 0
## 2 2020-03-02 East of England 1
## 3 2020-03-03 East of England 0
## 4 2020-03-04 East of England 0
## 5 2020-03-05 East of England 0
## 6 2020-03-06 East of England 1
## 7 2020-03-07 East of England 0
## 8 2020-03-08 East of England 0
## 9 2020-03-09 East of England 1
## 10 2020-03-10 East of England 0
## 11 2020-03-11 East of England 0
## 12 2020-03-12 East of England 0
## 13 2020-03-13 East of England 1
## 14 2020-03-14 East of England 2
## 15 2020-03-15 East of England 2
## 16 2020-03-16 East of England 1
## 17 2020-03-17 East of England 1
## 18 2020-03-18 East of England 5
## 19 2020-03-19 East of England 4
## 20 2020-03-20 East of England 2
## 21 2020-03-21 East of England 11
## 22 2020-03-22 East of England 12
## 23 2020-03-23 East of England 11
## 24 2020-03-24 East of England 19
## 25 2020-03-25 East of England 26
## 26 2020-03-26 East of England 36
## 27 2020-03-27 East of England 38
## 28 2020-03-28 East of England 28
## 29 2020-03-29 East of England 43
## 30 2020-03-30 East of England 45
## 31 2020-03-31 East of England 70
## 32 2020-04-01 East of England 62
## 33 2020-04-02 East of England 65
## 34 2020-04-03 East of England 80
## 35 2020-04-04 East of England 71
## 36 2020-04-05 East of England 76
## 37 2020-04-06 East of England 71
## 38 2020-04-07 East of England 93
## 39 2020-04-08 East of England 111
## 40 2020-04-09 East of England 87
## 41 2020-04-10 East of England 74
## 42 2020-04-11 East of England 92
## 43 2020-04-12 East of England 100
## 44 2020-04-13 East of England 78
## 45 2020-04-14 East of England 61
## 46 2020-04-15 East of England 82
## 47 2020-04-16 East of England 74
## 48 2020-04-17 East of England 86
## 49 2020-04-18 East of England 64
## 50 2020-04-19 East of England 67
## 51 2020-04-20 East of England 67
## 52 2020-04-21 East of England 75
## 53 2020-04-22 East of England 67
## 54 2020-04-23 East of England 49
## 55 2020-04-24 East of England 66
## 56 2020-04-25 East of England 54
## 57 2020-04-26 East of England 48
## 58 2020-04-27 East of England 46
## 59 2020-04-28 East of England 58
## 60 2020-04-29 East of England 32
## 61 2020-04-30 East of England 45
## 62 2020-05-01 East of England 49
## 63 2020-05-02 East of England 29
## 64 2020-05-03 East of England 41
## 65 2020-05-04 East of England 19
## 66 2020-05-05 East of England 36
## 67 2020-05-06 East of England 31
## 68 2020-05-07 East of England 33
## 69 2020-05-08 East of England 33
## 70 2020-05-09 East of England 29
## 71 2020-05-10 East of England 22
## 72 2020-05-11 East of England 18
## 73 2020-05-12 East of England 21
## 74 2020-05-13 East of England 27
## 75 2020-05-14 East of England 26
## 76 2020-05-15 East of England 19
## 77 2020-05-16 East of England 26
## 78 2020-05-17 East of England 17
## 79 2020-05-18 East of England 25
## 80 2020-05-19 East of England 15
## 81 2020-05-20 East of England 26
## 82 2020-05-21 East of England 21
## 83 2020-05-22 East of England 13
## 84 2020-05-23 East of England 12
## 85 2020-05-24 East of England 17
## 86 2020-05-25 East of England 25
## 87 2020-05-26 East of England 14
## 88 2020-05-27 East of England 12
## 89 2020-05-28 East of England 17
## 90 2020-05-29 East of England 16
## 91 2020-05-30 East of England 9
## 92 2020-05-31 East of England 8
## 93 2020-06-01 East of England 17
## 94 2020-06-02 East of England 14
## 95 2020-06-03 East of England 10
## 96 2020-06-04 East of England 7
## 97 2020-06-05 East of England 14
## 98 2020-06-06 East of England 5
## 99 2020-06-07 East of England 9
## 100 2020-06-08 East of England 7
## 101 2020-06-09 East of England 6
## 102 2020-06-10 East of England 8
## 103 2020-06-11 East of England 1
## 104 2020-06-12 East of England 9
## 105 2020-06-13 East of England 5
## 106 2020-06-14 East of England 4
## 107 2020-06-15 East of England 8
## 108 2020-06-16 East of England 3
## 109 2020-06-17 East of England 7
## 110 2020-06-18 East of England 4
## 111 2020-06-19 East of England 7
## 112 2020-06-20 East of England 4
## 113 2020-06-21 East of England 3
## 114 2020-06-22 East of England 6
## 115 2020-06-23 East of England 5
## 116 2020-06-24 East of England 4
## 117 2020-06-25 East of England 1
## 118 2020-06-26 East of England 5
## 119 2020-06-27 East of England 6
## 120 2020-06-28 East of England 8
## 121 2020-06-29 East of England 4
## 122 2020-06-30 East of England 5
## 123 2020-07-01 East of England 2
## 124 2020-07-02 East of England 5
## 125 2020-07-03 East of England 0
## 126 2020-07-04 East of England 3
## 127 2020-07-05 East of England 1
## 128 2020-07-06 East of England 2
## 129 2020-07-07 East of England 2
## 130 2020-07-08 East of England 0
## 131 2020-07-09 East of England 8
## 132 2020-07-10 East of England 4
## 133 2020-07-11 East of England 2
## 134 2020-07-12 East of England 1
## 135 2020-07-13 East of England 8
## 136 2020-07-14 East of England 2
## 137 2020-07-15 East of England 0
## 138 2020-07-16 East of England 0
## 139 2020-07-17 East of England 0
## 140 2020-07-18 East of England 0
## 141 2020-07-19 East of England 1
## 142 2020-07-20 East of England 1
## 143 2020-07-21 East of England 1
## 144 2020-07-22 East of England 2
## 145 2020-07-23 East of England 1
## 146 2020-07-24 East of England 1
## 147 2020-07-25 East of England 0
## 148 2020-07-26 East of England 1
## 149 2020-07-27 East of England 1
## 150 2020-07-28 East of England 2
## 151 2020-07-29 East of England 0
## 152 2020-07-30 East of England 0
## 153 2020-07-31 East of England 1
## 154 2020-08-01 East of England 0
## 155 2020-08-02 East of England 0
## 156 2020-08-03 East of England 0
## 157 2020-08-04 East of England 1
## 158 2020-08-05 East of England 1
## 159 2020-08-06 East of England 0
## 160 2020-08-07 East of England 1
## 161 2020-08-08 East of England 0
## 162 2020-08-09 East of England 0
## 163 2020-08-10 East of England 1
## 164 2020-08-11 East of England 2
## 165 2020-08-12 East of England 1
## 166 2020-08-13 East of England 0
## 167 2020-08-14 East of England 1
## 168 2020-08-15 East of England 1
## 169 2020-08-16 East of England 0
## 170 2020-08-17 East of England 0
## 171 2020-08-18 East of England 2
## 172 2020-08-19 East of England 1
## 173 2020-08-20 East of England 1
## 174 2020-08-21 East of England 0
## 175 2020-08-22 East of England 1
## 176 2020-08-23 East of England 1
## 177 2020-08-24 East of England 0
## 178 2020-08-25 East of England 0
## 179 2020-08-26 East of England 1
## 180 2020-08-27 East of England 1
## 181 2020-08-28 East of England 0
## 182 2020-08-29 East of England 0
## 183 2020-08-30 East of England 0
## 184 2020-08-31 East of England 0
## 185 2020-09-01 East of England 0
## 186 2020-09-02 East of England 0
## 187 2020-09-03 East of England 1
## 188 2020-09-04 East of England 1
## 189 2020-09-05 East of England 0
## 190 2020-09-06 East of England 1
## 191 2020-09-07 East of England 0
## 192 2020-09-08 East of England 0
## 193 2020-09-09 East of England 0
## 194 2020-09-10 East of England 0
## 195 2020-09-11 East of England 0
## 196 2020-09-12 East of England 0
## 197 2020-09-13 East of England 1
## 198 2020-09-14 East of England 1
## 199 2020-09-15 East of England 0
## 200 2020-09-16 East of England 0
## 201 2020-09-17 East of England 0
## 202 2020-09-18 East of England 0
## 203 2020-09-19 East of England 0
## 204 2020-09-20 East of England 2
## 205 2020-09-21 East of England 0
## 206 2020-09-22 East of England 2
## 207 2020-09-23 East of England 1
## 208 2020-09-24 East of England 0
## 209 2020-09-25 East of England 1
## 210 2020-09-26 East of England 1
## 211 2020-09-27 East of England 1
## 212 2020-09-28 East of England 2
## 213 2020-09-29 East of England 2
## 214 2020-09-30 East of England 2
## 215 2020-10-01 East of England 2
## 216 2020-10-02 East of England 1
## 217 2020-10-03 East of England 1
## 218 2020-10-04 East of England 0
## 219 2020-10-05 East of England 0
## 220 2020-10-06 East of England 4
## 221 2020-10-07 East of England 6
## 222 2020-10-08 East of England 3
## 223 2020-10-09 East of England 1
## 224 2020-10-10 East of England 6
## 225 2020-10-11 East of England 2
## 226 2020-10-12 East of England 2
## 227 2020-10-13 East of England 1
## 228 2020-10-14 East of England 3
## 229 2020-10-15 East of England 4
## 230 2020-10-16 East of England 5
## 231 2020-10-17 East of England 6
## 232 2020-10-18 East of England 7
## 233 2020-10-19 East of England 5
## 234 2020-10-20 East of England 9
## 235 2020-10-21 East of England 7
## 236 2020-10-22 East of England 7
## 237 2020-10-23 East of England 14
## 238 2020-10-24 East of England 1
## 239 2020-10-25 East of England 10
## 240 2020-10-26 East of England 10
## 241 2020-10-27 East of England 8
## 242 2020-10-28 East of England 12
## 243 2020-10-29 East of England 10
## 244 2020-10-30 East of England 12
## 245 2020-10-31 East of England 15
## 246 2020-11-01 East of England 14
## 247 2020-11-02 East of England 9
## 248 2020-11-03 East of England 14
## 249 2020-11-04 East of England 11
## 250 2020-11-05 East of England 12
## 251 2020-11-06 East of England 18
## 252 2020-11-07 East of England 10
## 253 2020-11-08 East of England 13
## 254 2020-11-09 East of England 16
## 255 2020-11-10 East of England 26
## 256 2020-11-11 East of England 14
## 257 2020-11-12 East of England 14
## 258 2020-11-13 East of England 21
## 259 2020-11-14 East of England 19
## 260 2020-11-15 East of England 13
## 261 2020-11-16 East of England 11
## 262 2020-11-17 East of England 17
## 263 2020-11-18 East of England 19
## 264 2020-11-19 East of England 23
## 265 2020-11-20 East of England 24
## 266 2020-11-21 East of England 19
## 267 2020-11-22 East of England 21
## 268 2020-11-23 East of England 18
## 269 2020-11-24 East of England 21
## 270 2020-11-25 East of England 19
## 271 2020-11-26 East of England 19
## 272 2020-11-27 East of England 14
## 273 2020-11-28 East of England 28
## 274 2020-11-29 East of England 19
## 275 2020-11-30 East of England 22
## 276 2020-12-01 East of England 25
## 277 2020-12-02 East of England 18
## 278 2020-12-03 East of England 23
## 279 2020-12-04 East of England 25
## 280 2020-12-05 East of England 25
## 281 2020-12-06 East of England 21
## 282 2020-12-07 East of England 16
## 283 2020-12-08 East of England 26
## 284 2020-12-09 East of England 19
## 285 2020-12-10 East of England 32
## 286 2020-12-11 East of England 32
## 287 2020-12-12 East of England 27
## 288 2020-12-13 East of England 25
## 289 2020-12-14 East of England 32
## 290 2020-12-15 East of England 35
## 291 2020-12-16 East of England 29
## 292 2020-12-17 East of England 42
## 293 2020-12-18 East of England 44
## 294 2020-12-19 East of England 54
## 295 2020-12-20 East of England 51
## 296 2020-12-21 East of England 66
## 297 2020-12-22 East of England 52
## 298 2020-12-23 East of England 61
## 299 2020-12-24 East of England 58
## 300 2020-12-25 East of England 57
## 301 2020-12-26 East of England 62
## 302 2020-12-27 East of England 53
## 303 2020-12-28 East of England 71
## 304 2020-12-29 East of England 53
## 305 2020-12-30 East of England 75
## 306 2020-12-31 East of England 82
## 307 2021-01-01 East of England 89
## 308 2021-01-02 East of England 66
## 309 2021-01-03 East of England 78
## 310 2021-01-04 East of England 87
## 311 2021-01-05 East of England 102
## 312 2021-01-06 East of England 99
## 313 2021-01-07 East of England 115
## 314 2021-01-08 East of England 93
## 315 2021-01-09 East of England 128
## 316 2021-01-10 East of England 120
## 317 2021-01-11 East of England 122
## 318 2021-01-12 East of England 128
## 319 2021-01-13 East of England 125
## 320 2021-01-14 East of England 123
## 321 2021-01-15 East of England 117
## 322 2021-01-16 East of England 127
## 323 2021-01-17 East of England 123
## 324 2021-01-18 East of England 119
## 325 2021-01-19 East of England 127
## 326 2021-01-20 East of England 144
## 327 2021-01-21 East of England 127
## 328 2021-01-22 East of England 118
## 329 2021-01-23 East of England 101
## 330 2021-01-24 East of England 99
## 331 2021-01-25 East of England 111
## 332 2021-01-26 East of England 85
## 333 2021-01-27 East of England 92
## 334 2021-01-28 East of England 109
## 335 2021-01-29 East of England 89
## 336 2021-01-30 East of England 74
## 337 2021-01-31 East of England 67
## 338 2021-02-01 East of England 59
## 339 2021-02-02 East of England 56
## 340 2021-02-03 East of England 47
## 341 2021-02-04 East of England 19
## 342 2020-03-01 London 0
## 343 2020-03-02 London 0
## 344 2020-03-03 London 0
## 345 2020-03-04 London 0
## 346 2020-03-05 London 0
## 347 2020-03-06 London 1
## 348 2020-03-07 London 0
## 349 2020-03-08 London 0
## 350 2020-03-09 London 1
## 351 2020-03-10 London 0
## 352 2020-03-11 London 5
## 353 2020-03-12 London 6
## 354 2020-03-13 London 10
## 355 2020-03-14 London 13
## 356 2020-03-15 London 9
## 357 2020-03-16 London 15
## 358 2020-03-17 London 23
## 359 2020-03-18 London 28
## 360 2020-03-19 London 25
## 361 2020-03-20 London 44
## 362 2020-03-21 London 49
## 363 2020-03-22 London 54
## 364 2020-03-23 London 63
## 365 2020-03-24 London 86
## 366 2020-03-25 London 112
## 367 2020-03-26 London 130
## 368 2020-03-27 London 130
## 369 2020-03-28 London 123
## 370 2020-03-29 London 145
## 371 2020-03-30 London 151
## 372 2020-03-31 London 183
## 373 2020-04-01 London 202
## 374 2020-04-02 London 191
## 375 2020-04-03 London 199
## 376 2020-04-04 London 231
## 377 2020-04-05 London 195
## 378 2020-04-06 London 198
## 379 2020-04-07 London 220
## 380 2020-04-08 London 239
## 381 2020-04-09 London 207
## 382 2020-04-10 London 171
## 383 2020-04-11 London 178
## 384 2020-04-12 London 159
## 385 2020-04-13 London 166
## 386 2020-04-14 London 143
## 387 2020-04-15 London 143
## 388 2020-04-16 London 140
## 389 2020-04-17 London 101
## 390 2020-04-18 London 101
## 391 2020-04-19 London 103
## 392 2020-04-20 London 96
## 393 2020-04-21 London 96
## 394 2020-04-22 London 109
## 395 2020-04-23 London 77
## 396 2020-04-24 London 71
## 397 2020-04-25 London 58
## 398 2020-04-26 London 53
## 399 2020-04-27 London 52
## 400 2020-04-28 London 44
## 401 2020-04-29 London 45
## 402 2020-04-30 London 40
## 403 2020-05-01 London 41
## 404 2020-05-02 London 41
## 405 2020-05-03 London 36
## 406 2020-05-04 London 30
## 407 2020-05-05 London 25
## 408 2020-05-06 London 37
## 409 2020-05-07 London 37
## 410 2020-05-08 London 31
## 411 2020-05-09 London 23
## 412 2020-05-10 London 26
## 413 2020-05-11 London 18
## 414 2020-05-12 London 18
## 415 2020-05-13 London 17
## 416 2020-05-14 London 20
## 417 2020-05-15 London 19
## 418 2020-05-16 London 14
## 419 2020-05-17 London 16
## 420 2020-05-18 London 11
## 421 2020-05-19 London 14
## 422 2020-05-20 London 19
## 423 2020-05-21 London 12
## 424 2020-05-22 London 10
## 425 2020-05-23 London 6
## 426 2020-05-24 London 7
## 427 2020-05-25 London 9
## 428 2020-05-26 London 14
## 429 2020-05-27 London 7
## 430 2020-05-28 London 8
## 431 2020-05-29 London 7
## 432 2020-05-30 London 12
## 433 2020-05-31 London 6
## 434 2020-06-01 London 10
## 435 2020-06-02 London 8
## 436 2020-06-03 London 6
## 437 2020-06-04 London 8
## 438 2020-06-05 London 4
## 439 2020-06-06 London 0
## 440 2020-06-07 London 5
## 441 2020-06-08 London 5
## 442 2020-06-09 London 5
## 443 2020-06-10 London 8
## 444 2020-06-11 London 5
## 445 2020-06-12 London 3
## 446 2020-06-13 London 3
## 447 2020-06-14 London 3
## 448 2020-06-15 London 1
## 449 2020-06-16 London 2
## 450 2020-06-17 London 1
## 451 2020-06-18 London 2
## 452 2020-06-19 London 5
## 453 2020-06-20 London 3
## 454 2020-06-21 London 4
## 455 2020-06-22 London 2
## 456 2020-06-23 London 1
## 457 2020-06-24 London 4
## 458 2020-06-25 London 3
## 459 2020-06-26 London 2
## 460 2020-06-27 London 1
## 461 2020-06-28 London 2
## 462 2020-06-29 London 2
## 463 2020-06-30 London 1
## 464 2020-07-01 London 3
## 465 2020-07-02 London 2
## 466 2020-07-03 London 2
## 467 2020-07-04 London 1
## 468 2020-07-05 London 3
## 469 2020-07-06 London 2
## 470 2020-07-07 London 1
## 471 2020-07-08 London 3
## 472 2020-07-09 London 4
## 473 2020-07-10 London 0
## 474 2020-07-11 London 1
## 475 2020-07-12 London 1
## 476 2020-07-13 London 1
## 477 2020-07-14 London 0
## 478 2020-07-15 London 2
## 479 2020-07-16 London 0
## 480 2020-07-17 London 0
## 481 2020-07-18 London 2
## 482 2020-07-19 London 0
## 483 2020-07-20 London 0
## 484 2020-07-21 London 1
## 485 2020-07-22 London 0
## 486 2020-07-23 London 2
## 487 2020-07-24 London 0
## 488 2020-07-25 London 1
## 489 2020-07-26 London 0
## 490 2020-07-27 London 1
## 491 2020-07-28 London 0
## 492 2020-07-29 London 0
## 493 2020-07-30 London 1
## 494 2020-07-31 London 0
## 495 2020-08-01 London 0
## 496 2020-08-02 London 3
## 497 2020-08-03 London 0
## 498 2020-08-04 London 0
## 499 2020-08-05 London 0
## 500 2020-08-06 London 1
## 501 2020-08-07 London 0
## 502 2020-08-08 London 0
## 503 2020-08-09 London 0
## 504 2020-08-10 London 0
## 505 2020-08-11 London 1
## 506 2020-08-12 London 0
## 507 2020-08-13 London 2
## 508 2020-08-14 London 0
## 509 2020-08-15 London 0
## 510 2020-08-16 London 0
## 511 2020-08-17 London 1
## 512 2020-08-18 London 1
## 513 2020-08-19 London 0
## 514 2020-08-20 London 1
## 515 2020-08-21 London 0
## 516 2020-08-22 London 0
## 517 2020-08-23 London 0
## 518 2020-08-24 London 1
## 519 2020-08-25 London 1
## 520 2020-08-26 London 0
## 521 2020-08-27 London 0
## 522 2020-08-28 London 0
## 523 2020-08-29 London 0
## 524 2020-08-30 London 0
## 525 2020-08-31 London 1
## 526 2020-09-01 London 0
## 527 2020-09-02 London 1
## 528 2020-09-03 London 1
## 529 2020-09-04 London 0
## 530 2020-09-05 London 0
## 531 2020-09-06 London 2
## 532 2020-09-07 London 0
## 533 2020-09-08 London 0
## 534 2020-09-09 London 0
## 535 2020-09-10 London 2
## 536 2020-09-11 London 1
## 537 2020-09-12 London 1
## 538 2020-09-13 London 0
## 539 2020-09-14 London 0
## 540 2020-09-15 London 1
## 541 2020-09-16 London 2
## 542 2020-09-17 London 2
## 543 2020-09-18 London 1
## 544 2020-09-19 London 3
## 545 2020-09-20 London 3
## 546 2020-09-21 London 2
## 547 2020-09-22 London 6
## 548 2020-09-23 London 4
## 549 2020-09-24 London 3
## 550 2020-09-25 London 1
## 551 2020-09-26 London 1
## 552 2020-09-27 London 1
## 553 2020-09-28 London 3
## 554 2020-09-29 London 7
## 555 2020-09-30 London 6
## 556 2020-10-01 London 4
## 557 2020-10-02 London 1
## 558 2020-10-03 London 3
## 559 2020-10-04 London 2
## 560 2020-10-05 London 7
## 561 2020-10-06 London 4
## 562 2020-10-07 London 6
## 563 2020-10-08 London 6
## 564 2020-10-09 London 7
## 565 2020-10-10 London 3
## 566 2020-10-11 London 5
## 567 2020-10-12 London 7
## 568 2020-10-13 London 4
## 569 2020-10-14 London 6
## 570 2020-10-15 London 13
## 571 2020-10-16 London 6
## 572 2020-10-17 London 2
## 573 2020-10-18 London 5
## 574 2020-10-19 London 11
## 575 2020-10-20 London 8
## 576 2020-10-21 London 14
## 577 2020-10-22 London 12
## 578 2020-10-23 London 7
## 579 2020-10-24 London 18
## 580 2020-10-25 London 10
## 581 2020-10-26 London 10
## 582 2020-10-27 London 12
## 583 2020-10-28 London 23
## 584 2020-10-29 London 14
## 585 2020-10-30 London 17
## 586 2020-10-31 London 7
## 587 2020-11-01 London 17
## 588 2020-11-02 London 16
## 589 2020-11-03 London 10
## 590 2020-11-04 London 18
## 591 2020-11-05 London 17
## 592 2020-11-06 London 12
## 593 2020-11-07 London 21
## 594 2020-11-08 London 15
## 595 2020-11-09 London 28
## 596 2020-11-10 London 14
## 597 2020-11-11 London 15
## 598 2020-11-12 London 16
## 599 2020-11-13 London 14
## 600 2020-11-14 London 21
## 601 2020-11-15 London 18
## 602 2020-11-16 London 29
## 603 2020-11-17 London 29
## 604 2020-11-18 London 23
## 605 2020-11-19 London 24
## 606 2020-11-20 London 20
## 607 2020-11-21 London 19
## 608 2020-11-22 London 29
## 609 2020-11-23 London 19
## 610 2020-11-24 London 27
## 611 2020-11-25 London 30
## 612 2020-11-26 London 25
## 613 2020-11-27 London 28
## 614 2020-11-28 London 23
## 615 2020-11-29 London 40
## 616 2020-11-30 London 19
## 617 2020-12-01 London 28
## 618 2020-12-02 London 30
## 619 2020-12-03 London 27
## 620 2020-12-04 London 30
## 621 2020-12-05 London 25
## 622 2020-12-06 London 25
## 623 2020-12-07 London 29
## 624 2020-12-08 London 35
## 625 2020-12-09 London 28
## 626 2020-12-10 London 31
## 627 2020-12-11 London 27
## 628 2020-12-12 London 33
## 629 2020-12-13 London 33
## 630 2020-12-14 London 38
## 631 2020-12-15 London 49
## 632 2020-12-16 London 36
## 633 2020-12-17 London 57
## 634 2020-12-18 London 42
## 635 2020-12-19 London 40
## 636 2020-12-20 London 53
## 637 2020-12-21 London 60
## 638 2020-12-22 London 57
## 639 2020-12-23 London 57
## 640 2020-12-24 London 65
## 641 2020-12-25 London 82
## 642 2020-12-26 London 82
## 643 2020-12-27 London 91
## 644 2020-12-28 London 89
## 645 2020-12-29 London 108
## 646 2020-12-30 London 99
## 647 2020-12-31 London 107
## 648 2021-01-01 London 112
## 649 2021-01-02 London 124
## 650 2021-01-03 London 106
## 651 2021-01-04 London 148
## 652 2021-01-05 London 143
## 653 2021-01-06 London 146
## 654 2021-01-07 London 157
## 655 2021-01-08 London 138
## 656 2021-01-09 London 145
## 657 2021-01-10 London 160
## 658 2021-01-11 London 158
## 659 2021-01-12 London 170
## 660 2021-01-13 London 165
## 661 2021-01-14 London 154
## 662 2021-01-15 London 144
## 663 2021-01-16 London 158
## 664 2021-01-17 London 168
## 665 2021-01-18 London 181
## 666 2021-01-19 London 179
## 667 2021-01-20 London 155
## 668 2021-01-21 London 178
## 669 2021-01-22 London 136
## 670 2021-01-23 London 140
## 671 2021-01-24 London 128
## 672 2021-01-25 London 125
## 673 2021-01-26 London 118
## 674 2021-01-27 London 111
## 675 2021-01-28 London 106
## 676 2021-01-29 London 94
## 677 2021-01-30 London 81
## 678 2021-01-31 London 84
## 679 2021-02-01 London 66
## 680 2021-02-02 London 77
## 681 2021-02-03 London 57
## 682 2021-02-04 London 9
## 683 2020-03-01 Midlands 0
## 684 2020-03-02 Midlands 0
## 685 2020-03-03 Midlands 1
## 686 2020-03-04 Midlands 0
## 687 2020-03-05 Midlands 0
## 688 2020-03-06 Midlands 0
## 689 2020-03-07 Midlands 0
## 690 2020-03-08 Midlands 2
## 691 2020-03-09 Midlands 1
## 692 2020-03-10 Midlands 0
## 693 2020-03-11 Midlands 2
## 694 2020-03-12 Midlands 6
## 695 2020-03-13 Midlands 5
## 696 2020-03-14 Midlands 4
## 697 2020-03-15 Midlands 5
## 698 2020-03-16 Midlands 11
## 699 2020-03-17 Midlands 8
## 700 2020-03-18 Midlands 13
## 701 2020-03-19 Midlands 8
## 702 2020-03-20 Midlands 28
## 703 2020-03-21 Midlands 13
## 704 2020-03-22 Midlands 31
## 705 2020-03-23 Midlands 33
## 706 2020-03-24 Midlands 41
## 707 2020-03-25 Midlands 48
## 708 2020-03-26 Midlands 64
## 709 2020-03-27 Midlands 72
## 710 2020-03-28 Midlands 89
## 711 2020-03-29 Midlands 92
## 712 2020-03-30 Midlands 90
## 713 2020-03-31 Midlands 123
## 714 2020-04-01 Midlands 140
## 715 2020-04-02 Midlands 142
## 716 2020-04-03 Midlands 124
## 717 2020-04-04 Midlands 151
## 718 2020-04-05 Midlands 164
## 719 2020-04-06 Midlands 140
## 720 2020-04-07 Midlands 123
## 721 2020-04-08 Midlands 186
## 722 2020-04-09 Midlands 140
## 723 2020-04-10 Midlands 127
## 724 2020-04-11 Midlands 142
## 725 2020-04-12 Midlands 139
## 726 2020-04-13 Midlands 120
## 727 2020-04-14 Midlands 116
## 728 2020-04-15 Midlands 147
## 729 2020-04-16 Midlands 102
## 730 2020-04-17 Midlands 118
## 731 2020-04-18 Midlands 115
## 732 2020-04-19 Midlands 93
## 733 2020-04-20 Midlands 107
## 734 2020-04-21 Midlands 86
## 735 2020-04-22 Midlands 78
## 736 2020-04-23 Midlands 103
## 737 2020-04-24 Midlands 79
## 738 2020-04-25 Midlands 72
## 739 2020-04-26 Midlands 81
## 740 2020-04-27 Midlands 74
## 741 2020-04-28 Midlands 68
## 742 2020-04-29 Midlands 53
## 743 2020-04-30 Midlands 56
## 744 2020-05-01 Midlands 64
## 745 2020-05-02 Midlands 51
## 746 2020-05-03 Midlands 52
## 747 2020-05-04 Midlands 61
## 748 2020-05-05 Midlands 59
## 749 2020-05-06 Midlands 59
## 750 2020-05-07 Midlands 48
## 751 2020-05-08 Midlands 34
## 752 2020-05-09 Midlands 37
## 753 2020-05-10 Midlands 42
## 754 2020-05-11 Midlands 33
## 755 2020-05-12 Midlands 45
## 756 2020-05-13 Midlands 40
## 757 2020-05-14 Midlands 39
## 758 2020-05-15 Midlands 40
## 759 2020-05-16 Midlands 34
## 760 2020-05-17 Midlands 31
## 761 2020-05-18 Midlands 36
## 762 2020-05-19 Midlands 35
## 763 2020-05-20 Midlands 36
## 764 2020-05-21 Midlands 32
## 765 2020-05-22 Midlands 27
## 766 2020-05-23 Midlands 34
## 767 2020-05-24 Midlands 20
## 768 2020-05-25 Midlands 26
## 769 2020-05-26 Midlands 33
## 770 2020-05-27 Midlands 29
## 771 2020-05-28 Midlands 28
## 772 2020-05-29 Midlands 20
## 773 2020-05-30 Midlands 21
## 774 2020-05-31 Midlands 22
## 775 2020-06-01 Midlands 20
## 776 2020-06-02 Midlands 22
## 777 2020-06-03 Midlands 24
## 778 2020-06-04 Midlands 16
## 779 2020-06-05 Midlands 21
## 780 2020-06-06 Midlands 20
## 781 2020-06-07 Midlands 17
## 782 2020-06-08 Midlands 16
## 783 2020-06-09 Midlands 18
## 784 2020-06-10 Midlands 15
## 785 2020-06-11 Midlands 13
## 786 2020-06-12 Midlands 12
## 787 2020-06-13 Midlands 6
## 788 2020-06-14 Midlands 18
## 789 2020-06-15 Midlands 12
## 790 2020-06-16 Midlands 15
## 791 2020-06-17 Midlands 11
## 792 2020-06-18 Midlands 15
## 793 2020-06-19 Midlands 10
## 794 2020-06-20 Midlands 15
## 795 2020-06-21 Midlands 14
## 796 2020-06-22 Midlands 14
## 797 2020-06-23 Midlands 16
## 798 2020-06-24 Midlands 15
## 799 2020-06-25 Midlands 18
## 800 2020-06-26 Midlands 5
## 801 2020-06-27 Midlands 5
## 802 2020-06-28 Midlands 7
## 803 2020-06-29 Midlands 6
## 804 2020-06-30 Midlands 6
## 805 2020-07-01 Midlands 7
## 806 2020-07-02 Midlands 10
## 807 2020-07-03 Midlands 3
## 808 2020-07-04 Midlands 4
## 809 2020-07-05 Midlands 6
## 810 2020-07-06 Midlands 5
## 811 2020-07-07 Midlands 3
## 812 2020-07-08 Midlands 5
## 813 2020-07-09 Midlands 9
## 814 2020-07-10 Midlands 3
## 815 2020-07-11 Midlands 0
## 816 2020-07-12 Midlands 5
## 817 2020-07-13 Midlands 1
## 818 2020-07-14 Midlands 1
## 819 2020-07-15 Midlands 6
## 820 2020-07-16 Midlands 2
## 821 2020-07-17 Midlands 3
## 822 2020-07-18 Midlands 3
## 823 2020-07-19 Midlands 3
## 824 2020-07-20 Midlands 3
## 825 2020-07-21 Midlands 1
## 826 2020-07-22 Midlands 2
## 827 2020-07-23 Midlands 6
## 828 2020-07-24 Midlands 1
## 829 2020-07-25 Midlands 4
## 830 2020-07-26 Midlands 4
## 831 2020-07-27 Midlands 5
## 832 2020-07-28 Midlands 1
## 833 2020-07-29 Midlands 1
## 834 2020-07-30 Midlands 1
## 835 2020-07-31 Midlands 2
## 836 2020-08-01 Midlands 0
## 837 2020-08-02 Midlands 1
## 838 2020-08-03 Midlands 2
## 839 2020-08-04 Midlands 1
## 840 2020-08-05 Midlands 1
## 841 2020-08-06 Midlands 0
## 842 2020-08-07 Midlands 3
## 843 2020-08-08 Midlands 2
## 844 2020-08-09 Midlands 0
## 845 2020-08-10 Midlands 0
## 846 2020-08-11 Midlands 2
## 847 2020-08-12 Midlands 0
## 848 2020-08-13 Midlands 0
## 849 2020-08-14 Midlands 0
## 850 2020-08-15 Midlands 1
## 851 2020-08-16 Midlands 0
## 852 2020-08-17 Midlands 0
## 853 2020-08-18 Midlands 0
## 854 2020-08-19 Midlands 0
## 855 2020-08-20 Midlands 0
## 856 2020-08-21 Midlands 1
## 857 2020-08-22 Midlands 0
## 858 2020-08-23 Midlands 0
## 859 2020-08-24 Midlands 0
## 860 2020-08-25 Midlands 2
## 861 2020-08-26 Midlands 3
## 862 2020-08-27 Midlands 2
## 863 2020-08-28 Midlands 1
## 864 2020-08-29 Midlands 0
## 865 2020-08-30 Midlands 2
## 866 2020-08-31 Midlands 1
## 867 2020-09-01 Midlands 0
## 868 2020-09-02 Midlands 2
## 869 2020-09-03 Midlands 0
## 870 2020-09-04 Midlands 0
## 871 2020-09-05 Midlands 0
## 872 2020-09-06 Midlands 1
## 873 2020-09-07 Midlands 1
## 874 2020-09-08 Midlands 3
## 875 2020-09-09 Midlands 0
## 876 2020-09-10 Midlands 1
## 877 2020-09-11 Midlands 1
## 878 2020-09-12 Midlands 2
## 879 2020-09-13 Midlands 4
## 880 2020-09-14 Midlands 1
## 881 2020-09-15 Midlands 2
## 882 2020-09-16 Midlands 3
## 883 2020-09-17 Midlands 2
## 884 2020-09-18 Midlands 5
## 885 2020-09-19 Midlands 2
## 886 2020-09-20 Midlands 7
## 887 2020-09-21 Midlands 3
## 888 2020-09-22 Midlands 4
## 889 2020-09-23 Midlands 10
## 890 2020-09-24 Midlands 7
## 891 2020-09-25 Midlands 4
## 892 2020-09-26 Midlands 5
## 893 2020-09-27 Midlands 9
## 894 2020-09-28 Midlands 6
## 895 2020-09-29 Midlands 4
## 896 2020-09-30 Midlands 5
## 897 2020-10-01 Midlands 8
## 898 2020-10-02 Midlands 7
## 899 2020-10-03 Midlands 6
## 900 2020-10-04 Midlands 7
## 901 2020-10-05 Midlands 6
## 902 2020-10-06 Midlands 5
## 903 2020-10-07 Midlands 9
## 904 2020-10-08 Midlands 8
## 905 2020-10-09 Midlands 7
## 906 2020-10-10 Midlands 2
## 907 2020-10-11 Midlands 15
## 908 2020-10-12 Midlands 7
## 909 2020-10-13 Midlands 16
## 910 2020-10-14 Midlands 12
## 911 2020-10-15 Midlands 11
## 912 2020-10-16 Midlands 18
## 913 2020-10-17 Midlands 25
## 914 2020-10-18 Midlands 11
## 915 2020-10-19 Midlands 14
## 916 2020-10-20 Midlands 19
## 917 2020-10-21 Midlands 15
## 918 2020-10-22 Midlands 34
## 919 2020-10-23 Midlands 32
## 920 2020-10-24 Midlands 24
## 921 2020-10-25 Midlands 30
## 922 2020-10-26 Midlands 33
## 923 2020-10-27 Midlands 38
## 924 2020-10-28 Midlands 30
## 925 2020-10-29 Midlands 42
## 926 2020-10-30 Midlands 42
## 927 2020-10-31 Midlands 50
## 928 2020-11-01 Midlands 44
## 929 2020-11-02 Midlands 58
## 930 2020-11-03 Midlands 37
## 931 2020-11-04 Midlands 67
## 932 2020-11-05 Midlands 50
## 933 2020-11-06 Midlands 43
## 934 2020-11-07 Midlands 60
## 935 2020-11-08 Midlands 55
## 936 2020-11-09 Midlands 67
## 937 2020-11-10 Midlands 68
## 938 2020-11-11 Midlands 58
## 939 2020-11-12 Midlands 64
## 940 2020-11-13 Midlands 47
## 941 2020-11-14 Midlands 66
## 942 2020-11-15 Midlands 72
## 943 2020-11-16 Midlands 66
## 944 2020-11-17 Midlands 66
## 945 2020-11-18 Midlands 83
## 946 2020-11-19 Midlands 72
## 947 2020-11-20 Midlands 87
## 948 2020-11-21 Midlands 59
## 949 2020-11-22 Midlands 84
## 950 2020-11-23 Midlands 80
## 951 2020-11-24 Midlands 73
## 952 2020-11-25 Midlands 74
## 953 2020-11-26 Midlands 77
## 954 2020-11-27 Midlands 78
## 955 2020-11-28 Midlands 80
## 956 2020-11-29 Midlands 86
## 957 2020-11-30 Midlands 79
## 958 2020-12-01 Midlands 74
## 959 2020-12-02 Midlands 64
## 960 2020-12-03 Midlands 82
## 961 2020-12-04 Midlands 67
## 962 2020-12-05 Midlands 71
## 963 2020-12-06 Midlands 75
## 964 2020-12-07 Midlands 68
## 965 2020-12-08 Midlands 66
## 966 2020-12-09 Midlands 63
## 967 2020-12-10 Midlands 75
## 968 2020-12-11 Midlands 65
## 969 2020-12-12 Midlands 81
## 970 2020-12-13 Midlands 78
## 971 2020-12-14 Midlands 77
## 972 2020-12-15 Midlands 73
## 973 2020-12-16 Midlands 73
## 974 2020-12-17 Midlands 86
## 975 2020-12-18 Midlands 80
## 976 2020-12-19 Midlands 57
## 977 2020-12-20 Midlands 66
## 978 2020-12-21 Midlands 85
## 979 2020-12-22 Midlands 74
## 980 2020-12-23 Midlands 58
## 981 2020-12-24 Midlands 67
## 982 2020-12-25 Midlands 78
## 983 2020-12-26 Midlands 73
## 984 2020-12-27 Midlands 86
## 985 2020-12-28 Midlands 63
## 986 2020-12-29 Midlands 82
## 987 2020-12-30 Midlands 100
## 988 2020-12-31 Midlands 88
## 989 2021-01-01 Midlands 77
## 990 2021-01-02 Midlands 74
## 991 2021-01-03 Midlands 71
## 992 2021-01-04 Midlands 93
## 993 2021-01-05 Midlands 104
## 994 2021-01-06 Midlands 110
## 995 2021-01-07 Midlands 103
## 996 2021-01-08 Midlands 131
## 997 2021-01-09 Midlands 137
## 998 2021-01-10 Midlands 119
## 999 2021-01-11 Midlands 142
## 1000 2021-01-12 Midlands 158
## 1001 2021-01-13 Midlands 140
## 1002 2021-01-14 Midlands 155
## 1003 2021-01-15 Midlands 130
## 1004 2021-01-16 Midlands 150
## 1005 2021-01-17 Midlands 154
## 1006 2021-01-18 Midlands 158
## 1007 2021-01-19 Midlands 156
## 1008 2021-01-20 Midlands 143
## 1009 2021-01-21 Midlands 154
## 1010 2021-01-22 Midlands 157
## 1011 2021-01-23 Midlands 140
## 1012 2021-01-24 Midlands 161
## 1013 2021-01-25 Midlands 154
## 1014 2021-01-26 Midlands 137
## 1015 2021-01-27 Midlands 136
## 1016 2021-01-28 Midlands 131
## 1017 2021-01-29 Midlands 138
## 1018 2021-01-30 Midlands 115
## 1019 2021-01-31 Midlands 102
## 1020 2021-02-01 Midlands 124
## 1021 2021-02-02 Midlands 114
## 1022 2021-02-03 Midlands 92
## 1023 2021-02-04 Midlands 6
## 1024 2020-03-01 North East and Yorkshire 0
## 1025 2020-03-02 North East and Yorkshire 0
## 1026 2020-03-03 North East and Yorkshire 0
## 1027 2020-03-04 North East and Yorkshire 0
## 1028 2020-03-05 North East and Yorkshire 0
## 1029 2020-03-06 North East and Yorkshire 0
## 1030 2020-03-07 North East and Yorkshire 0
## 1031 2020-03-08 North East and Yorkshire 0
## 1032 2020-03-09 North East and Yorkshire 0
## 1033 2020-03-10 North East and Yorkshire 0
## 1034 2020-03-11 North East and Yorkshire 0
## 1035 2020-03-12 North East and Yorkshire 0
## 1036 2020-03-13 North East and Yorkshire 0
## 1037 2020-03-14 North East and Yorkshire 0
## 1038 2020-03-15 North East and Yorkshire 2
## 1039 2020-03-16 North East and Yorkshire 3
## 1040 2020-03-17 North East and Yorkshire 1
## 1041 2020-03-18 North East and Yorkshire 2
## 1042 2020-03-19 North East and Yorkshire 6
## 1043 2020-03-20 North East and Yorkshire 5
## 1044 2020-03-21 North East and Yorkshire 6
## 1045 2020-03-22 North East and Yorkshire 7
## 1046 2020-03-23 North East and Yorkshire 9
## 1047 2020-03-24 North East and Yorkshire 8
## 1048 2020-03-25 North East and Yorkshire 18
## 1049 2020-03-26 North East and Yorkshire 21
## 1050 2020-03-27 North East and Yorkshire 28
## 1051 2020-03-28 North East and Yorkshire 35
## 1052 2020-03-29 North East and Yorkshire 38
## 1053 2020-03-30 North East and Yorkshire 64
## 1054 2020-03-31 North East and Yorkshire 60
## 1055 2020-04-01 North East and Yorkshire 67
## 1056 2020-04-02 North East and Yorkshire 75
## 1057 2020-04-03 North East and Yorkshire 100
## 1058 2020-04-04 North East and Yorkshire 105
## 1059 2020-04-05 North East and Yorkshire 92
## 1060 2020-04-06 North East and Yorkshire 96
## 1061 2020-04-07 North East and Yorkshire 102
## 1062 2020-04-08 North East and Yorkshire 107
## 1063 2020-04-09 North East and Yorkshire 111
## 1064 2020-04-10 North East and Yorkshire 117
## 1065 2020-04-11 North East and Yorkshire 98
## 1066 2020-04-12 North East and Yorkshire 84
## 1067 2020-04-13 North East and Yorkshire 94
## 1068 2020-04-14 North East and Yorkshire 107
## 1069 2020-04-15 North East and Yorkshire 96
## 1070 2020-04-16 North East and Yorkshire 103
## 1071 2020-04-17 North East and Yorkshire 88
## 1072 2020-04-18 North East and Yorkshire 95
## 1073 2020-04-19 North East and Yorkshire 88
## 1074 2020-04-20 North East and Yorkshire 100
## 1075 2020-04-21 North East and Yorkshire 76
## 1076 2020-04-22 North East and Yorkshire 84
## 1077 2020-04-23 North East and Yorkshire 63
## 1078 2020-04-24 North East and Yorkshire 72
## 1079 2020-04-25 North East and Yorkshire 69
## 1080 2020-04-26 North East and Yorkshire 65
## 1081 2020-04-27 North East and Yorkshire 65
## 1082 2020-04-28 North East and Yorkshire 57
## 1083 2020-04-29 North East and Yorkshire 69
## 1084 2020-04-30 North East and Yorkshire 57
## 1085 2020-05-01 North East and Yorkshire 64
## 1086 2020-05-02 North East and Yorkshire 48
## 1087 2020-05-03 North East and Yorkshire 40
## 1088 2020-05-04 North East and Yorkshire 49
## 1089 2020-05-05 North East and Yorkshire 40
## 1090 2020-05-06 North East and Yorkshire 51
## 1091 2020-05-07 North East and Yorkshire 45
## 1092 2020-05-08 North East and Yorkshire 42
## 1093 2020-05-09 North East and Yorkshire 44
## 1094 2020-05-10 North East and Yorkshire 40
## 1095 2020-05-11 North East and Yorkshire 29
## 1096 2020-05-12 North East and Yorkshire 27
## 1097 2020-05-13 North East and Yorkshire 28
## 1098 2020-05-14 North East and Yorkshire 31
## 1099 2020-05-15 North East and Yorkshire 32
## 1100 2020-05-16 North East and Yorkshire 35
## 1101 2020-05-17 North East and Yorkshire 26
## 1102 2020-05-18 North East and Yorkshire 30
## 1103 2020-05-19 North East and Yorkshire 27
## 1104 2020-05-20 North East and Yorkshire 22
## 1105 2020-05-21 North East and Yorkshire 33
## 1106 2020-05-22 North East and Yorkshire 22
## 1107 2020-05-23 North East and Yorkshire 18
## 1108 2020-05-24 North East and Yorkshire 26
## 1109 2020-05-25 North East and Yorkshire 21
## 1110 2020-05-26 North East and Yorkshire 21
## 1111 2020-05-27 North East and Yorkshire 23
## 1112 2020-05-28 North East and Yorkshire 21
## 1113 2020-05-29 North East and Yorkshire 25
## 1114 2020-05-30 North East and Yorkshire 20
## 1115 2020-05-31 North East and Yorkshire 20
## 1116 2020-06-01 North East and Yorkshire 17
## 1117 2020-06-02 North East and Yorkshire 23
## 1118 2020-06-03 North East and Yorkshire 24
## 1119 2020-06-04 North East and Yorkshire 17
## 1120 2020-06-05 North East and Yorkshire 18
## 1121 2020-06-06 North East and Yorkshire 21
## 1122 2020-06-07 North East and Yorkshire 14
## 1123 2020-06-08 North East and Yorkshire 11
## 1124 2020-06-09 North East and Yorkshire 12
## 1125 2020-06-10 North East and Yorkshire 19
## 1126 2020-06-11 North East and Yorkshire 7
## 1127 2020-06-12 North East and Yorkshire 9
## 1128 2020-06-13 North East and Yorkshire 10
## 1129 2020-06-14 North East and Yorkshire 11
## 1130 2020-06-15 North East and Yorkshire 9
## 1131 2020-06-16 North East and Yorkshire 10
## 1132 2020-06-17 North East and Yorkshire 9
## 1133 2020-06-18 North East and Yorkshire 11
## 1134 2020-06-19 North East and Yorkshire 6
## 1135 2020-06-20 North East and Yorkshire 5
## 1136 2020-06-21 North East and Yorkshire 4
## 1137 2020-06-22 North East and Yorkshire 7
## 1138 2020-06-23 North East and Yorkshire 8
## 1139 2020-06-24 North East and Yorkshire 10
## 1140 2020-06-25 North East and Yorkshire 4
## 1141 2020-06-26 North East and Yorkshire 8
## 1142 2020-06-27 North East and Yorkshire 4
## 1143 2020-06-28 North East and Yorkshire 5
## 1144 2020-06-29 North East and Yorkshire 2
## 1145 2020-06-30 North East and Yorkshire 7
## 1146 2020-07-01 North East and Yorkshire 1
## 1147 2020-07-02 North East and Yorkshire 5
## 1148 2020-07-03 North East and Yorkshire 4
## 1149 2020-07-04 North East and Yorkshire 4
## 1150 2020-07-05 North East and Yorkshire 3
## 1151 2020-07-06 North East and Yorkshire 2
## 1152 2020-07-07 North East and Yorkshire 3
## 1153 2020-07-08 North East and Yorkshire 3
## 1154 2020-07-09 North East and Yorkshire 0
## 1155 2020-07-10 North East and Yorkshire 3
## 1156 2020-07-11 North East and Yorkshire 1
## 1157 2020-07-12 North East and Yorkshire 4
## 1158 2020-07-13 North East and Yorkshire 1
## 1159 2020-07-14 North East and Yorkshire 1
## 1160 2020-07-15 North East and Yorkshire 2
## 1161 2020-07-16 North East and Yorkshire 3
## 1162 2020-07-17 North East and Yorkshire 1
## 1163 2020-07-18 North East and Yorkshire 2
## 1164 2020-07-19 North East and Yorkshire 2
## 1165 2020-07-20 North East and Yorkshire 1
## 1166 2020-07-21 North East and Yorkshire 1
## 1167 2020-07-22 North East and Yorkshire 6
## 1168 2020-07-23 North East and Yorkshire 0
## 1169 2020-07-24 North East and Yorkshire 1
## 1170 2020-07-25 North East and Yorkshire 5
## 1171 2020-07-26 North East and Yorkshire 1
## 1172 2020-07-27 North East and Yorkshire 0
## 1173 2020-07-28 North East and Yorkshire 2
## 1174 2020-07-29 North East and Yorkshire 1
## 1175 2020-07-30 North East and Yorkshire 0
## 1176 2020-07-31 North East and Yorkshire 1
## 1177 2020-08-01 North East and Yorkshire 3
## 1178 2020-08-02 North East and Yorkshire 2
## 1179 2020-08-03 North East and Yorkshire 1
## 1180 2020-08-04 North East and Yorkshire 3
## 1181 2020-08-05 North East and Yorkshire 1
## 1182 2020-08-06 North East and Yorkshire 4
## 1183 2020-08-07 North East and Yorkshire 0
## 1184 2020-08-08 North East and Yorkshire 2
## 1185 2020-08-09 North East and Yorkshire 3
## 1186 2020-08-10 North East and Yorkshire 3
## 1187 2020-08-11 North East and Yorkshire 2
## 1188 2020-08-12 North East and Yorkshire 2
## 1189 2020-08-13 North East and Yorkshire 0
## 1190 2020-08-14 North East and Yorkshire 1
## 1191 2020-08-15 North East and Yorkshire 1
## 1192 2020-08-16 North East and Yorkshire 0
## 1193 2020-08-17 North East and Yorkshire 6
## 1194 2020-08-18 North East and Yorkshire 1
## 1195 2020-08-19 North East and Yorkshire 0
## 1196 2020-08-20 North East and Yorkshire 0
## 1197 2020-08-21 North East and Yorkshire 1
## 1198 2020-08-22 North East and Yorkshire 1
## 1199 2020-08-23 North East and Yorkshire 3
## 1200 2020-08-24 North East and Yorkshire 0
## 1201 2020-08-25 North East and Yorkshire 2
## 1202 2020-08-26 North East and Yorkshire 2
## 1203 2020-08-27 North East and Yorkshire 1
## 1204 2020-08-28 North East and Yorkshire 0
## 1205 2020-08-29 North East and Yorkshire 1
## 1206 2020-08-30 North East and Yorkshire 0
## 1207 2020-08-31 North East and Yorkshire 0
## 1208 2020-09-01 North East and Yorkshire 2
## 1209 2020-09-02 North East and Yorkshire 3
## 1210 2020-09-03 North East and Yorkshire 1
## 1211 2020-09-04 North East and Yorkshire 1
## 1212 2020-09-05 North East and Yorkshire 2
## 1213 2020-09-06 North East and Yorkshire 1
## 1214 2020-09-07 North East and Yorkshire 0
## 1215 2020-09-08 North East and Yorkshire 1
## 1216 2020-09-09 North East and Yorkshire 2
## 1217 2020-09-10 North East and Yorkshire 0
## 1218 2020-09-11 North East and Yorkshire 3
## 1219 2020-09-12 North East and Yorkshire 1
## 1220 2020-09-13 North East and Yorkshire 3
## 1221 2020-09-14 North East and Yorkshire 4
## 1222 2020-09-15 North East and Yorkshire 3
## 1223 2020-09-16 North East and Yorkshire 3
## 1224 2020-09-17 North East and Yorkshire 5
## 1225 2020-09-18 North East and Yorkshire 6
## 1226 2020-09-19 North East and Yorkshire 2
## 1227 2020-09-20 North East and Yorkshire 9
## 1228 2020-09-21 North East and Yorkshire 7
## 1229 2020-09-22 North East and Yorkshire 5
## 1230 2020-09-23 North East and Yorkshire 6
## 1231 2020-09-24 North East and Yorkshire 3
## 1232 2020-09-25 North East and Yorkshire 5
## 1233 2020-09-26 North East and Yorkshire 7
## 1234 2020-09-27 North East and Yorkshire 10
## 1235 2020-09-28 North East and Yorkshire 6
## 1236 2020-09-29 North East and Yorkshire 7
## 1237 2020-09-30 North East and Yorkshire 7
## 1238 2020-10-01 North East and Yorkshire 8
## 1239 2020-10-02 North East and Yorkshire 16
## 1240 2020-10-03 North East and Yorkshire 12
## 1241 2020-10-04 North East and Yorkshire 13
## 1242 2020-10-05 North East and Yorkshire 10
## 1243 2020-10-06 North East and Yorkshire 15
## 1244 2020-10-07 North East and Yorkshire 13
## 1245 2020-10-08 North East and Yorkshire 16
## 1246 2020-10-09 North East and Yorkshire 10
## 1247 2020-10-10 North East and Yorkshire 16
## 1248 2020-10-11 North East and Yorkshire 16
## 1249 2020-10-12 North East and Yorkshire 15
## 1250 2020-10-13 North East and Yorkshire 21
## 1251 2020-10-14 North East and Yorkshire 20
## 1252 2020-10-15 North East and Yorkshire 23
## 1253 2020-10-16 North East and Yorkshire 24
## 1254 2020-10-17 North East and Yorkshire 34
## 1255 2020-10-18 North East and Yorkshire 22
## 1256 2020-10-19 North East and Yorkshire 34
## 1257 2020-10-20 North East and Yorkshire 37
## 1258 2020-10-21 North East and Yorkshire 43
## 1259 2020-10-22 North East and Yorkshire 33
## 1260 2020-10-23 North East and Yorkshire 31
## 1261 2020-10-24 North East and Yorkshire 34
## 1262 2020-10-25 North East and Yorkshire 35
## 1263 2020-10-26 North East and Yorkshire 46
## 1264 2020-10-27 North East and Yorkshire 45
## 1265 2020-10-28 North East and Yorkshire 39
## 1266 2020-10-29 North East and Yorkshire 51
## 1267 2020-10-30 North East and Yorkshire 48
## 1268 2020-10-31 North East and Yorkshire 58
## 1269 2020-11-01 North East and Yorkshire 48
## 1270 2020-11-02 North East and Yorkshire 50
## 1271 2020-11-03 North East and Yorkshire 48
## 1272 2020-11-04 North East and Yorkshire 57
## 1273 2020-11-05 North East and Yorkshire 57
## 1274 2020-11-06 North East and Yorkshire 57
## 1275 2020-11-07 North East and Yorkshire 75
## 1276 2020-11-08 North East and Yorkshire 62
## 1277 2020-11-09 North East and Yorkshire 87
## 1278 2020-11-10 North East and Yorkshire 65
## 1279 2020-11-11 North East and Yorkshire 59
## 1280 2020-11-12 North East and Yorkshire 77
## 1281 2020-11-13 North East and Yorkshire 78
## 1282 2020-11-14 North East and Yorkshire 72
## 1283 2020-11-15 North East and Yorkshire 77
## 1284 2020-11-16 North East and Yorkshire 52
## 1285 2020-11-17 North East and Yorkshire 68
## 1286 2020-11-18 North East and Yorkshire 81
## 1287 2020-11-19 North East and Yorkshire 72
## 1288 2020-11-20 North East and Yorkshire 75
## 1289 2020-11-21 North East and Yorkshire 54
## 1290 2020-11-22 North East and Yorkshire 80
## 1291 2020-11-23 North East and Yorkshire 84
## 1292 2020-11-24 North East and Yorkshire 81
## 1293 2020-11-25 North East and Yorkshire 70
## 1294 2020-11-26 North East and Yorkshire 64
## 1295 2020-11-27 North East and Yorkshire 62
## 1296 2020-11-28 North East and Yorkshire 77
## 1297 2020-11-29 North East and Yorkshire 61
## 1298 2020-11-30 North East and Yorkshire 56
## 1299 2020-12-01 North East and Yorkshire 44
## 1300 2020-12-02 North East and Yorkshire 59
## 1301 2020-12-03 North East and Yorkshire 71
## 1302 2020-12-04 North East and Yorkshire 65
## 1303 2020-12-05 North East and Yorkshire 48
## 1304 2020-12-06 North East and Yorkshire 64
## 1305 2020-12-07 North East and Yorkshire 49
## 1306 2020-12-08 North East and Yorkshire 54
## 1307 2020-12-09 North East and Yorkshire 49
## 1308 2020-12-10 North East and Yorkshire 55
## 1309 2020-12-11 North East and Yorkshire 56
## 1310 2020-12-12 North East and Yorkshire 55
## 1311 2020-12-13 North East and Yorkshire 51
## 1312 2020-12-14 North East and Yorkshire 49
## 1313 2020-12-15 North East and Yorkshire 55
## 1314 2020-12-16 North East and Yorkshire 40
## 1315 2020-12-17 North East and Yorkshire 49
## 1316 2020-12-18 North East and Yorkshire 58
## 1317 2020-12-19 North East and Yorkshire 49
## 1318 2020-12-20 North East and Yorkshire 52
## 1319 2020-12-21 North East and Yorkshire 35
## 1320 2020-12-22 North East and Yorkshire 57
## 1321 2020-12-23 North East and Yorkshire 56
## 1322 2020-12-24 North East and Yorkshire 48
## 1323 2020-12-25 North East and Yorkshire 56
## 1324 2020-12-26 North East and Yorkshire 65
## 1325 2020-12-27 North East and Yorkshire 67
## 1326 2020-12-28 North East and Yorkshire 61
## 1327 2020-12-29 North East and Yorkshire 57
## 1328 2020-12-30 North East and Yorkshire 41
## 1329 2020-12-31 North East and Yorkshire 49
## 1330 2021-01-01 North East and Yorkshire 68
## 1331 2021-01-02 North East and Yorkshire 56
## 1332 2021-01-03 North East and Yorkshire 48
## 1333 2021-01-04 North East and Yorkshire 61
## 1334 2021-01-05 North East and Yorkshire 62
## 1335 2021-01-06 North East and Yorkshire 59
## 1336 2021-01-07 North East and Yorkshire 68
## 1337 2021-01-08 North East and Yorkshire 66
## 1338 2021-01-09 North East and Yorkshire 53
## 1339 2021-01-10 North East and Yorkshire 77
## 1340 2021-01-11 North East and Yorkshire 78
## 1341 2021-01-12 North East and Yorkshire 61
## 1342 2021-01-13 North East and Yorkshire 68
## 1343 2021-01-14 North East and Yorkshire 65
## 1344 2021-01-15 North East and Yorkshire 84
## 1345 2021-01-16 North East and Yorkshire 95
## 1346 2021-01-17 North East and Yorkshire 71
## 1347 2021-01-18 North East and Yorkshire 76
## 1348 2021-01-19 North East and Yorkshire 100
## 1349 2021-01-20 North East and Yorkshire 86
## 1350 2021-01-21 North East and Yorkshire 84
## 1351 2021-01-22 North East and Yorkshire 73
## 1352 2021-01-23 North East and Yorkshire 61
## 1353 2021-01-24 North East and Yorkshire 60
## 1354 2021-01-25 North East and Yorkshire 74
## 1355 2021-01-26 North East and Yorkshire 69
## 1356 2021-01-27 North East and Yorkshire 62
## 1357 2021-01-28 North East and Yorkshire 65
## 1358 2021-01-29 North East and Yorkshire 74
## 1359 2021-01-30 North East and Yorkshire 66
## 1360 2021-01-31 North East and Yorkshire 72
## 1361 2021-02-01 North East and Yorkshire 70
## 1362 2021-02-02 North East and Yorkshire 61
## 1363 2021-02-03 North East and Yorkshire 54
## 1364 2021-02-04 North East and Yorkshire 13
## 1365 2020-03-01 North West 0
## 1366 2020-03-02 North West 0
## 1367 2020-03-03 North West 0
## 1368 2020-03-04 North West 0
## 1369 2020-03-05 North West 1
## 1370 2020-03-06 North West 0
## 1371 2020-03-07 North West 0
## 1372 2020-03-08 North West 1
## 1373 2020-03-09 North West 0
## 1374 2020-03-10 North West 0
## 1375 2020-03-11 North West 0
## 1376 2020-03-12 North West 2
## 1377 2020-03-13 North West 3
## 1378 2020-03-14 North West 1
## 1379 2020-03-15 North West 4
## 1380 2020-03-16 North West 2
## 1381 2020-03-17 North West 4
## 1382 2020-03-18 North West 6
## 1383 2020-03-19 North West 7
## 1384 2020-03-20 North West 10
## 1385 2020-03-21 North West 11
## 1386 2020-03-22 North West 13
## 1387 2020-03-23 North West 15
## 1388 2020-03-24 North West 21
## 1389 2020-03-25 North West 21
## 1390 2020-03-26 North West 29
## 1391 2020-03-27 North West 36
## 1392 2020-03-28 North West 28
## 1393 2020-03-29 North West 46
## 1394 2020-03-30 North West 67
## 1395 2020-03-31 North West 52
## 1396 2020-04-01 North West 86
## 1397 2020-04-02 North West 96
## 1398 2020-04-03 North West 95
## 1399 2020-04-04 North West 98
## 1400 2020-04-05 North West 102
## 1401 2020-04-06 North West 100
## 1402 2020-04-07 North West 136
## 1403 2020-04-08 North West 127
## 1404 2020-04-09 North West 119
## 1405 2020-04-10 North West 117
## 1406 2020-04-11 North West 138
## 1407 2020-04-12 North West 125
## 1408 2020-04-13 North West 130
## 1409 2020-04-14 North West 130
## 1410 2020-04-15 North West 114
## 1411 2020-04-16 North West 135
## 1412 2020-04-17 North West 98
## 1413 2020-04-18 North West 113
## 1414 2020-04-19 North West 71
## 1415 2020-04-20 North West 83
## 1416 2020-04-21 North West 76
## 1417 2020-04-22 North West 86
## 1418 2020-04-23 North West 85
## 1419 2020-04-24 North West 66
## 1420 2020-04-25 North West 66
## 1421 2020-04-26 North West 55
## 1422 2020-04-27 North West 54
## 1423 2020-04-28 North West 57
## 1424 2020-04-29 North West 63
## 1425 2020-04-30 North West 60
## 1426 2020-05-01 North West 45
## 1427 2020-05-02 North West 56
## 1428 2020-05-03 North West 55
## 1429 2020-05-04 North West 48
## 1430 2020-05-05 North West 48
## 1431 2020-05-06 North West 44
## 1432 2020-05-07 North West 49
## 1433 2020-05-08 North West 42
## 1434 2020-05-09 North West 31
## 1435 2020-05-10 North West 42
## 1436 2020-05-11 North West 35
## 1437 2020-05-12 North West 38
## 1438 2020-05-13 North West 25
## 1439 2020-05-14 North West 26
## 1440 2020-05-15 North West 33
## 1441 2020-05-16 North West 32
## 1442 2020-05-17 North West 24
## 1443 2020-05-18 North West 31
## 1444 2020-05-19 North West 35
## 1445 2020-05-20 North West 27
## 1446 2020-05-21 North West 28
## 1447 2020-05-22 North West 26
## 1448 2020-05-23 North West 31
## 1449 2020-05-24 North West 26
## 1450 2020-05-25 North West 31
## 1451 2020-05-26 North West 27
## 1452 2020-05-27 North West 27
## 1453 2020-05-28 North West 28
## 1454 2020-05-29 North West 20
## 1455 2020-05-30 North West 19
## 1456 2020-05-31 North West 13
## 1457 2020-06-01 North West 12
## 1458 2020-06-02 North West 27
## 1459 2020-06-03 North West 22
## 1460 2020-06-04 North West 22
## 1461 2020-06-05 North West 16
## 1462 2020-06-06 North West 26
## 1463 2020-06-07 North West 20
## 1464 2020-06-08 North West 23
## 1465 2020-06-09 North West 17
## 1466 2020-06-10 North West 16
## 1467 2020-06-11 North West 16
## 1468 2020-06-12 North West 11
## 1469 2020-06-13 North West 10
## 1470 2020-06-14 North West 15
## 1471 2020-06-15 North West 16
## 1472 2020-06-16 North West 16
## 1473 2020-06-17 North West 13
## 1474 2020-06-18 North West 14
## 1475 2020-06-19 North West 7
## 1476 2020-06-20 North West 11
## 1477 2020-06-21 North West 8
## 1478 2020-06-22 North West 11
## 1479 2020-06-23 North West 13
## 1480 2020-06-24 North West 13
## 1481 2020-06-25 North West 15
## 1482 2020-06-26 North West 6
## 1483 2020-06-27 North West 7
## 1484 2020-06-28 North West 9
## 1485 2020-06-29 North West 9
## 1486 2020-06-30 North West 7
## 1487 2020-07-01 North West 3
## 1488 2020-07-02 North West 6
## 1489 2020-07-03 North West 7
## 1490 2020-07-04 North West 4
## 1491 2020-07-05 North West 6
## 1492 2020-07-06 North West 9
## 1493 2020-07-07 North West 8
## 1494 2020-07-08 North West 5
## 1495 2020-07-09 North West 10
## 1496 2020-07-10 North West 2
## 1497 2020-07-11 North West 5
## 1498 2020-07-12 North West 0
## 1499 2020-07-13 North West 6
## 1500 2020-07-14 North West 4
## 1501 2020-07-15 North West 5
## 1502 2020-07-16 North West 2
## 1503 2020-07-17 North West 4
## 1504 2020-07-18 North West 5
## 1505 2020-07-19 North West 3
## 1506 2020-07-20 North West 0
## 1507 2020-07-21 North West 2
## 1508 2020-07-22 North West 3
## 1509 2020-07-23 North West 3
## 1510 2020-07-24 North West 1
## 1511 2020-07-25 North West 1
## 1512 2020-07-26 North West 3
## 1513 2020-07-27 North West 1
## 1514 2020-07-28 North West 1
## 1515 2020-07-29 North West 2
## 1516 2020-07-30 North West 2
## 1517 2020-07-31 North West 0
## 1518 2020-08-01 North West 2
## 1519 2020-08-02 North West 1
## 1520 2020-08-03 North West 8
## 1521 2020-08-04 North West 3
## 1522 2020-08-05 North West 2
## 1523 2020-08-06 North West 2
## 1524 2020-08-07 North West 2
## 1525 2020-08-08 North West 2
## 1526 2020-08-09 North West 3
## 1527 2020-08-10 North West 2
## 1528 2020-08-11 North West 3
## 1529 2020-08-12 North West 0
## 1530 2020-08-13 North West 2
## 1531 2020-08-14 North West 2
## 1532 2020-08-15 North West 6
## 1533 2020-08-16 North West 2
## 1534 2020-08-17 North West 1
## 1535 2020-08-18 North West 2
## 1536 2020-08-19 North West 1
## 1537 2020-08-20 North West 1
## 1538 2020-08-21 North West 4
## 1539 2020-08-22 North West 3
## 1540 2020-08-23 North West 5
## 1541 2020-08-24 North West 4
## 1542 2020-08-25 North West 3
## 1543 2020-08-26 North West 4
## 1544 2020-08-27 North West 1
## 1545 2020-08-28 North West 2
## 1546 2020-08-29 North West 0
## 1547 2020-08-30 North West 2
## 1548 2020-08-31 North West 3
## 1549 2020-09-01 North West 0
## 1550 2020-09-02 North West 2
## 1551 2020-09-03 North West 1
## 1552 2020-09-04 North West 3
## 1553 2020-09-05 North West 6
## 1554 2020-09-06 North West 1
## 1555 2020-09-07 North West 8
## 1556 2020-09-08 North West 6
## 1557 2020-09-09 North West 5
## 1558 2020-09-10 North West 5
## 1559 2020-09-11 North West 1
## 1560 2020-09-12 North West 4
## 1561 2020-09-13 North West 2
## 1562 2020-09-14 North West 4
## 1563 2020-09-15 North West 4
## 1564 2020-09-16 North West 6
## 1565 2020-09-17 North West 7
## 1566 2020-09-18 North West 6
## 1567 2020-09-19 North West 3
## 1568 2020-09-20 North West 2
## 1569 2020-09-21 North West 2
## 1570 2020-09-22 North West 9
## 1571 2020-09-23 North West 14
## 1572 2020-09-24 North West 10
## 1573 2020-09-25 North West 8
## 1574 2020-09-26 North West 14
## 1575 2020-09-27 North West 11
## 1576 2020-09-28 North West 15
## 1577 2020-09-29 North West 12
## 1578 2020-09-30 North West 17
## 1579 2020-10-01 North West 17
## 1580 2020-10-02 North West 20
## 1581 2020-10-03 North West 15
## 1582 2020-10-04 North West 15
## 1583 2020-10-05 North West 15
## 1584 2020-10-06 North West 20
## 1585 2020-10-07 North West 20
## 1586 2020-10-08 North West 22
## 1587 2020-10-09 North West 23
## 1588 2020-10-10 North West 31
## 1589 2020-10-11 North West 31
## 1590 2020-10-12 North West 35
## 1591 2020-10-13 North West 26
## 1592 2020-10-14 North West 35
## 1593 2020-10-15 North West 36
## 1594 2020-10-16 North West 34
## 1595 2020-10-17 North West 52
## 1596 2020-10-18 North West 40
## 1597 2020-10-19 North West 43
## 1598 2020-10-20 North West 48
## 1599 2020-10-21 North West 51
## 1600 2020-10-22 North West 49
## 1601 2020-10-23 North West 50
## 1602 2020-10-24 North West 51
## 1603 2020-10-25 North West 63
## 1604 2020-10-26 North West 53
## 1605 2020-10-27 North West 49
## 1606 2020-10-28 North West 57
## 1607 2020-10-29 North West 74
## 1608 2020-10-30 North West 73
## 1609 2020-10-31 North West 63
## 1610 2020-11-01 North West 76
## 1611 2020-11-02 North West 65
## 1612 2020-11-03 North West 76
## 1613 2020-11-04 North West 64
## 1614 2020-11-05 North West 67
## 1615 2020-11-06 North West 75
## 1616 2020-11-07 North West 79
## 1617 2020-11-08 North West 83
## 1618 2020-11-09 North West 82
## 1619 2020-11-10 North West 68
## 1620 2020-11-11 North West 61
## 1621 2020-11-12 North West 64
## 1622 2020-11-13 North West 81
## 1623 2020-11-14 North West 61
## 1624 2020-11-15 North West 75
## 1625 2020-11-16 North West 74
## 1626 2020-11-17 North West 73
## 1627 2020-11-18 North West 71
## 1628 2020-11-19 North West 67
## 1629 2020-11-20 North West 52
## 1630 2020-11-21 North West 68
## 1631 2020-11-22 North West 52
## 1632 2020-11-23 North West 54
## 1633 2020-11-24 North West 64
## 1634 2020-11-25 North West 65
## 1635 2020-11-26 North West 53
## 1636 2020-11-27 North West 51
## 1637 2020-11-28 North West 46
## 1638 2020-11-29 North West 54
## 1639 2020-11-30 North West 48
## 1640 2020-12-01 North West 53
## 1641 2020-12-02 North West 48
## 1642 2020-12-03 North West 46
## 1643 2020-12-04 North West 48
## 1644 2020-12-05 North West 37
## 1645 2020-12-06 North West 43
## 1646 2020-12-07 North West 50
## 1647 2020-12-08 North West 49
## 1648 2020-12-09 North West 48
## 1649 2020-12-10 North West 49
## 1650 2020-12-11 North West 41
## 1651 2020-12-12 North West 48
## 1652 2020-12-13 North West 41
## 1653 2020-12-14 North West 51
## 1654 2020-12-15 North West 34
## 1655 2020-12-16 North West 41
## 1656 2020-12-17 North West 25
## 1657 2020-12-18 North West 47
## 1658 2020-12-19 North West 45
## 1659 2020-12-20 North West 37
## 1660 2020-12-21 North West 51
## 1661 2020-12-22 North West 52
## 1662 2020-12-23 North West 50
## 1663 2020-12-24 North West 58
## 1664 2020-12-25 North West 52
## 1665 2020-12-26 North West 56
## 1666 2020-12-27 North West 50
## 1667 2020-12-28 North West 48
## 1668 2020-12-29 North West 48
## 1669 2020-12-30 North West 49
## 1670 2020-12-31 North West 62
## 1671 2021-01-01 North West 54
## 1672 2021-01-02 North West 55
## 1673 2021-01-03 North West 55
## 1674 2021-01-04 North West 50
## 1675 2021-01-05 North West 55
## 1676 2021-01-06 North West 67
## 1677 2021-01-07 North West 61
## 1678 2021-01-08 North West 63
## 1679 2021-01-09 North West 64
## 1680 2021-01-10 North West 64
## 1681 2021-01-11 North West 77
## 1682 2021-01-12 North West 58
## 1683 2021-01-13 North West 84
## 1684 2021-01-14 North West 91
## 1685 2021-01-15 North West 82
## 1686 2021-01-16 North West 81
## 1687 2021-01-17 North West 79
## 1688 2021-01-18 North West 92
## 1689 2021-01-19 North West 88
## 1690 2021-01-20 North West 85
## 1691 2021-01-21 North West 83
## 1692 2021-01-22 North West 104
## 1693 2021-01-23 North West 99
## 1694 2021-01-24 North West 91
## 1695 2021-01-25 North West 82
## 1696 2021-01-26 North West 94
## 1697 2021-01-27 North West 101
## 1698 2021-01-28 North West 96
## 1699 2021-01-29 North West 90
## 1700 2021-01-30 North West 67
## 1701 2021-01-31 North West 80
## 1702 2021-02-01 North West 86
## 1703 2021-02-02 North West 66
## 1704 2021-02-03 North West 41
## 1705 2021-02-04 North West 15
## 1706 2020-03-01 South East 0
## 1707 2020-03-02 South East 0
## 1708 2020-03-03 South East 1
## 1709 2020-03-04 South East 0
## 1710 2020-03-05 South East 1
## 1711 2020-03-06 South East 0
## 1712 2020-03-07 South East 0
## 1713 2020-03-08 South East 1
## 1714 2020-03-09 South East 1
## 1715 2020-03-10 South East 1
## 1716 2020-03-11 South East 1
## 1717 2020-03-12 South East 0
## 1718 2020-03-13 South East 1
## 1719 2020-03-14 South East 1
## 1720 2020-03-15 South East 5
## 1721 2020-03-16 South East 8
## 1722 2020-03-17 South East 7
## 1723 2020-03-18 South East 10
## 1724 2020-03-19 South East 9
## 1725 2020-03-20 South East 13
## 1726 2020-03-21 South East 7
## 1727 2020-03-22 South East 25
## 1728 2020-03-23 South East 20
## 1729 2020-03-24 South East 22
## 1730 2020-03-25 South East 29
## 1731 2020-03-26 South East 35
## 1732 2020-03-27 South East 36
## 1733 2020-03-28 South East 36
## 1734 2020-03-29 South East 55
## 1735 2020-03-30 South East 58
## 1736 2020-03-31 South East 65
## 1737 2020-04-01 South East 66
## 1738 2020-04-02 South East 55
## 1739 2020-04-03 South East 72
## 1740 2020-04-04 South East 80
## 1741 2020-04-05 South East 82
## 1742 2020-04-06 South East 88
## 1743 2020-04-07 South East 100
## 1744 2020-04-08 South East 83
## 1745 2020-04-09 South East 104
## 1746 2020-04-10 South East 88
## 1747 2020-04-11 South East 88
## 1748 2020-04-12 South East 88
## 1749 2020-04-13 South East 84
## 1750 2020-04-14 South East 65
## 1751 2020-04-15 South East 72
## 1752 2020-04-16 South East 56
## 1753 2020-04-17 South East 86
## 1754 2020-04-18 South East 57
## 1755 2020-04-19 South East 70
## 1756 2020-04-20 South East 87
## 1757 2020-04-21 South East 51
## 1758 2020-04-22 South East 54
## 1759 2020-04-23 South East 57
## 1760 2020-04-24 South East 64
## 1761 2020-04-25 South East 51
## 1762 2020-04-26 South East 51
## 1763 2020-04-27 South East 41
## 1764 2020-04-28 South East 40
## 1765 2020-04-29 South East 47
## 1766 2020-04-30 South East 29
## 1767 2020-05-01 South East 37
## 1768 2020-05-02 South East 36
## 1769 2020-05-03 South East 17
## 1770 2020-05-04 South East 35
## 1771 2020-05-05 South East 29
## 1772 2020-05-06 South East 25
## 1773 2020-05-07 South East 27
## 1774 2020-05-08 South East 26
## 1775 2020-05-09 South East 28
## 1776 2020-05-10 South East 19
## 1777 2020-05-11 South East 25
## 1778 2020-05-12 South East 27
## 1779 2020-05-13 South East 18
## 1780 2020-05-14 South East 32
## 1781 2020-05-15 South East 25
## 1782 2020-05-16 South East 22
## 1783 2020-05-17 South East 18
## 1784 2020-05-18 South East 23
## 1785 2020-05-19 South East 12
## 1786 2020-05-20 South East 22
## 1787 2020-05-21 South East 15
## 1788 2020-05-22 South East 17
## 1789 2020-05-23 South East 21
## 1790 2020-05-24 South East 17
## 1791 2020-05-25 South East 13
## 1792 2020-05-26 South East 19
## 1793 2020-05-27 South East 19
## 1794 2020-05-28 South East 12
## 1795 2020-05-29 South East 22
## 1796 2020-05-30 South East 8
## 1797 2020-05-31 South East 12
## 1798 2020-06-01 South East 11
## 1799 2020-06-02 South East 13
## 1800 2020-06-03 South East 18
## 1801 2020-06-04 South East 11
## 1802 2020-06-05 South East 11
## 1803 2020-06-06 South East 10
## 1804 2020-06-07 South East 12
## 1805 2020-06-08 South East 8
## 1806 2020-06-09 South East 11
## 1807 2020-06-10 South East 11
## 1808 2020-06-11 South East 5
## 1809 2020-06-12 South East 6
## 1810 2020-06-13 South East 7
## 1811 2020-06-14 South East 7
## 1812 2020-06-15 South East 8
## 1813 2020-06-16 South East 14
## 1814 2020-06-17 South East 10
## 1815 2020-06-18 South East 4
## 1816 2020-06-19 South East 7
## 1817 2020-06-20 South East 5
## 1818 2020-06-21 South East 3
## 1819 2020-06-22 South East 2
## 1820 2020-06-23 South East 9
## 1821 2020-06-24 South East 7
## 1822 2020-06-25 South East 5
## 1823 2020-06-26 South East 8
## 1824 2020-06-27 South East 9
## 1825 2020-06-28 South East 6
## 1826 2020-06-29 South East 5
## 1827 2020-06-30 South East 5
## 1828 2020-07-01 South East 2
## 1829 2020-07-02 South East 8
## 1830 2020-07-03 South East 3
## 1831 2020-07-04 South East 6
## 1832 2020-07-05 South East 5
## 1833 2020-07-06 South East 4
## 1834 2020-07-07 South East 6
## 1835 2020-07-08 South East 3
## 1836 2020-07-09 South East 7
## 1837 2020-07-10 South East 3
## 1838 2020-07-11 South East 4
## 1839 2020-07-12 South East 5
## 1840 2020-07-13 South East 5
## 1841 2020-07-14 South East 5
## 1842 2020-07-15 South East 6
## 1843 2020-07-16 South East 3
## 1844 2020-07-17 South East 1
## 1845 2020-07-18 South East 5
## 1846 2020-07-19 South East 2
## 1847 2020-07-20 South East 6
## 1848 2020-07-21 South East 4
## 1849 2020-07-22 South East 2
## 1850 2020-07-23 South East 3
## 1851 2020-07-24 South East 1
## 1852 2020-07-25 South East 1
## 1853 2020-07-26 South East 3
## 1854 2020-07-27 South East 1
## 1855 2020-07-28 South East 3
## 1856 2020-07-29 South East 2
## 1857 2020-07-30 South East 3
## 1858 2020-07-31 South East 1
## 1859 2020-08-01 South East 2
## 1860 2020-08-02 South East 4
## 1861 2020-08-03 South East 0
## 1862 2020-08-04 South East 0
## 1863 2020-08-05 South East 0
## 1864 2020-08-06 South East 2
## 1865 2020-08-07 South East 0
## 1866 2020-08-08 South East 2
## 1867 2020-08-09 South East 0
## 1868 2020-08-10 South East 2
## 1869 2020-08-11 South East 1
## 1870 2020-08-12 South East 1
## 1871 2020-08-13 South East 0
## 1872 2020-08-14 South East 0
## 1873 2020-08-15 South East 2
## 1874 2020-08-16 South East 1
## 1875 2020-08-17 South East 0
## 1876 2020-08-18 South East 2
## 1877 2020-08-19 South East 1
## 1878 2020-08-20 South East 0
## 1879 2020-08-21 South East 0
## 1880 2020-08-22 South East 0
## 1881 2020-08-23 South East 1
## 1882 2020-08-24 South East 0
## 1883 2020-08-25 South East 1
## 1884 2020-08-26 South East 0
## 1885 2020-08-27 South East 1
## 1886 2020-08-28 South East 2
## 1887 2020-08-29 South East 1
## 1888 2020-08-30 South East 0
## 1889 2020-08-31 South East 2
## 1890 2020-09-01 South East 1
## 1891 2020-09-02 South East 1
## 1892 2020-09-03 South East 0
## 1893 2020-09-04 South East 1
## 1894 2020-09-05 South East 0
## 1895 2020-09-06 South East 1
## 1896 2020-09-07 South East 0
## 1897 2020-09-08 South East 0
## 1898 2020-09-09 South East 0
## 1899 2020-09-10 South East 1
## 1900 2020-09-11 South East 1
## 1901 2020-09-12 South East 0
## 1902 2020-09-13 South East 3
## 1903 2020-09-14 South East 1
## 1904 2020-09-15 South East 2
## 1905 2020-09-16 South East 2
## 1906 2020-09-17 South East 3
## 1907 2020-09-18 South East 1
## 1908 2020-09-19 South East 1
## 1909 2020-09-20 South East 0
## 1910 2020-09-21 South East 3
## 1911 2020-09-22 South East 0
## 1912 2020-09-23 South East 2
## 1913 2020-09-24 South East 1
## 1914 2020-09-25 South East 3
## 1915 2020-09-26 South East 2
## 1916 2020-09-27 South East 2
## 1917 2020-09-28 South East 6
## 1918 2020-09-29 South East 3
## 1919 2020-09-30 South East 4
## 1920 2020-10-01 South East 4
## 1921 2020-10-02 South East 2
## 1922 2020-10-03 South East 1
## 1923 2020-10-04 South East 1
## 1924 2020-10-05 South East 2
## 1925 2020-10-06 South East 1
## 1926 2020-10-07 South East 4
## 1927 2020-10-08 South East 1
## 1928 2020-10-09 South East 1
## 1929 2020-10-10 South East 3
## 1930 2020-10-11 South East 3
## 1931 2020-10-12 South East 4
## 1932 2020-10-13 South East 2
## 1933 2020-10-14 South East 2
## 1934 2020-10-15 South East 3
## 1935 2020-10-16 South East 2
## 1936 2020-10-17 South East 3
## 1937 2020-10-18 South East 4
## 1938 2020-10-19 South East 7
## 1939 2020-10-20 South East 8
## 1940 2020-10-21 South East 9
## 1941 2020-10-22 South East 5
## 1942 2020-10-23 South East 7
## 1943 2020-10-24 South East 5
## 1944 2020-10-25 South East 9
## 1945 2020-10-26 South East 13
## 1946 2020-10-27 South East 10
## 1947 2020-10-28 South East 10
## 1948 2020-10-29 South East 7
## 1949 2020-10-30 South East 6
## 1950 2020-10-31 South East 15
## 1951 2020-11-01 South East 18
## 1952 2020-11-02 South East 13
## 1953 2020-11-03 South East 16
## 1954 2020-11-04 South East 10
## 1955 2020-11-05 South East 10
## 1956 2020-11-06 South East 16
## 1957 2020-11-07 South East 17
## 1958 2020-11-08 South East 18
## 1959 2020-11-09 South East 19
## 1960 2020-11-10 South East 20
## 1961 2020-11-11 South East 20
## 1962 2020-11-12 South East 20
## 1963 2020-11-13 South East 12
## 1964 2020-11-14 South East 24
## 1965 2020-11-15 South East 25
## 1966 2020-11-16 South East 22
## 1967 2020-11-17 South East 23
## 1968 2020-11-18 South East 26
## 1969 2020-11-19 South East 21
## 1970 2020-11-20 South East 18
## 1971 2020-11-21 South East 23
## 1972 2020-11-22 South East 30
## 1973 2020-11-23 South East 29
## 1974 2020-11-24 South East 26
## 1975 2020-11-25 South East 42
## 1976 2020-11-26 South East 30
## 1977 2020-11-27 South East 31
## 1978 2020-11-28 South East 24
## 1979 2020-11-29 South East 37
## 1980 2020-11-30 South East 23
## 1981 2020-12-01 South East 29
## 1982 2020-12-02 South East 33
## 1983 2020-12-03 South East 36
## 1984 2020-12-04 South East 41
## 1985 2020-12-05 South East 36
## 1986 2020-12-06 South East 32
## 1987 2020-12-07 South East 25
## 1988 2020-12-08 South East 43
## 1989 2020-12-09 South East 44
## 1990 2020-12-10 South East 38
## 1991 2020-12-11 South East 48
## 1992 2020-12-12 South East 40
## 1993 2020-12-13 South East 41
## 1994 2020-12-14 South East 38
## 1995 2020-12-15 South East 50
## 1996 2020-12-16 South East 45
## 1997 2020-12-17 South East 54
## 1998 2020-12-18 South East 48
## 1999 2020-12-19 South East 42
## 2000 2020-12-20 South East 57
## 2001 2020-12-21 South East 66
## 2002 2020-12-22 South East 62
## 2003 2020-12-23 South East 70
## 2004 2020-12-24 South East 56
## 2005 2020-12-25 South East 71
## 2006 2020-12-26 South East 75
## 2007 2020-12-27 South East 76
## 2008 2020-12-28 South East 81
## 2009 2020-12-29 South East 78
## 2010 2020-12-30 South East 91
## 2011 2020-12-31 South East 91
## 2012 2021-01-01 South East 60
## 2013 2021-01-02 South East 94
## 2014 2021-01-03 South East 79
## 2015 2021-01-04 South East 105
## 2016 2021-01-05 South East 105
## 2017 2021-01-06 South East 121
## 2018 2021-01-07 South East 113
## 2019 2021-01-08 South East 123
## 2020 2021-01-09 South East 114
## 2021 2021-01-10 South East 122
## 2022 2021-01-11 South East 128
## 2023 2021-01-12 South East 166
## 2024 2021-01-13 South East 128
## 2025 2021-01-14 South East 136
## 2026 2021-01-15 South East 125
## 2027 2021-01-16 South East 149
## 2028 2021-01-17 South East 161
## 2029 2021-01-18 South East 146
## 2030 2021-01-19 South East 152
## 2031 2021-01-20 South East 133
## 2032 2021-01-21 South East 126
## 2033 2021-01-22 South East 128
## 2034 2021-01-23 South East 118
## 2035 2021-01-24 South East 115
## 2036 2021-01-25 South East 112
## 2037 2021-01-26 South East 130
## 2038 2021-01-27 South East 110
## 2039 2021-01-28 South East 127
## 2040 2021-01-29 South East 104
## 2041 2021-01-30 South East 89
## 2042 2021-01-31 South East 87
## 2043 2021-02-01 South East 77
## 2044 2021-02-02 South East 66
## 2045 2021-02-03 South East 63
## 2046 2021-02-04 South East 3
## 2047 2020-03-01 South West 0
## 2048 2020-03-02 South West 0
## 2049 2020-03-03 South West 0
## 2050 2020-03-04 South West 0
## 2051 2020-03-05 South West 0
## 2052 2020-03-06 South West 0
## 2053 2020-03-07 South West 0
## 2054 2020-03-08 South West 0
## 2055 2020-03-09 South West 0
## 2056 2020-03-10 South West 0
## 2057 2020-03-11 South West 1
## 2058 2020-03-12 South West 0
## 2059 2020-03-13 South West 0
## 2060 2020-03-14 South West 1
## 2061 2020-03-15 South West 0
## 2062 2020-03-16 South West 0
## 2063 2020-03-17 South West 2
## 2064 2020-03-18 South West 2
## 2065 2020-03-19 South West 4
## 2066 2020-03-20 South West 3
## 2067 2020-03-21 South West 6
## 2068 2020-03-22 South West 7
## 2069 2020-03-23 South West 8
## 2070 2020-03-24 South West 7
## 2071 2020-03-25 South West 9
## 2072 2020-03-26 South West 11
## 2073 2020-03-27 South West 13
## 2074 2020-03-28 South West 21
## 2075 2020-03-29 South West 18
## 2076 2020-03-30 South West 23
## 2077 2020-03-31 South West 23
## 2078 2020-04-01 South West 21
## 2079 2020-04-02 South West 23
## 2080 2020-04-03 South West 30
## 2081 2020-04-04 South West 42
## 2082 2020-04-05 South West 32
## 2083 2020-04-06 South West 34
## 2084 2020-04-07 South West 39
## 2085 2020-04-08 South West 47
## 2086 2020-04-09 South West 24
## 2087 2020-04-10 South West 46
## 2088 2020-04-11 South West 43
## 2089 2020-04-12 South West 23
## 2090 2020-04-13 South West 27
## 2091 2020-04-14 South West 24
## 2092 2020-04-15 South West 32
## 2093 2020-04-16 South West 29
## 2094 2020-04-17 South West 33
## 2095 2020-04-18 South West 25
## 2096 2020-04-19 South West 31
## 2097 2020-04-20 South West 26
## 2098 2020-04-21 South West 26
## 2099 2020-04-22 South West 23
## 2100 2020-04-23 South West 17
## 2101 2020-04-24 South West 19
## 2102 2020-04-25 South West 15
## 2103 2020-04-26 South West 27
## 2104 2020-04-27 South West 13
## 2105 2020-04-28 South West 17
## 2106 2020-04-29 South West 15
## 2107 2020-04-30 South West 26
## 2108 2020-05-01 South West 6
## 2109 2020-05-02 South West 7
## 2110 2020-05-03 South West 10
## 2111 2020-05-04 South West 17
## 2112 2020-05-05 South West 14
## 2113 2020-05-06 South West 19
## 2114 2020-05-07 South West 16
## 2115 2020-05-08 South West 6
## 2116 2020-05-09 South West 11
## 2117 2020-05-10 South West 5
## 2118 2020-05-11 South West 8
## 2119 2020-05-12 South West 7
## 2120 2020-05-13 South West 7
## 2121 2020-05-14 South West 6
## 2122 2020-05-15 South West 4
## 2123 2020-05-16 South West 4
## 2124 2020-05-17 South West 6
## 2125 2020-05-18 South West 4
## 2126 2020-05-19 South West 6
## 2127 2020-05-20 South West 1
## 2128 2020-05-21 South West 9
## 2129 2020-05-22 South West 7
## 2130 2020-05-23 South West 6
## 2131 2020-05-24 South West 3
## 2132 2020-05-25 South West 8
## 2133 2020-05-26 South West 11
## 2134 2020-05-27 South West 5
## 2135 2020-05-28 South West 10
## 2136 2020-05-29 South West 7
## 2137 2020-05-30 South West 3
## 2138 2020-05-31 South West 2
## 2139 2020-06-01 South West 7
## 2140 2020-06-02 South West 2
## 2141 2020-06-03 South West 7
## 2142 2020-06-04 South West 2
## 2143 2020-06-05 South West 2
## 2144 2020-06-06 South West 1
## 2145 2020-06-07 South West 3
## 2146 2020-06-08 South West 3
## 2147 2020-06-09 South West 0
## 2148 2020-06-10 South West 1
## 2149 2020-06-11 South West 2
## 2150 2020-06-12 South West 2
## 2151 2020-06-13 South West 2
## 2152 2020-06-14 South West 0
## 2153 2020-06-15 South West 2
## 2154 2020-06-16 South West 2
## 2155 2020-06-17 South West 0
## 2156 2020-06-18 South West 0
## 2157 2020-06-19 South West 0
## 2158 2020-06-20 South West 2
## 2159 2020-06-21 South West 0
## 2160 2020-06-22 South West 1
## 2161 2020-06-23 South West 1
## 2162 2020-06-24 South West 1
## 2163 2020-06-25 South West 0
## 2164 2020-06-26 South West 3
## 2165 2020-06-27 South West 0
## 2166 2020-06-28 South West 0
## 2167 2020-06-29 South West 1
## 2168 2020-06-30 South West 0
## 2169 2020-07-01 South West 0
## 2170 2020-07-02 South West 0
## 2171 2020-07-03 South West 0
## 2172 2020-07-04 South West 0
## 2173 2020-07-05 South West 1
## 2174 2020-07-06 South West 0
## 2175 2020-07-07 South West 0
## 2176 2020-07-08 South West 2
## 2177 2020-07-09 South West 0
## 2178 2020-07-10 South West 1
## 2179 2020-07-11 South West 0
## 2180 2020-07-12 South West 0
## 2181 2020-07-13 South West 1
## 2182 2020-07-14 South West 0
## 2183 2020-07-15 South West 0
## 2184 2020-07-16 South West 0
## 2185 2020-07-17 South West 1
## 2186 2020-07-18 South West 0
## 2187 2020-07-19 South West 0
## 2188 2020-07-20 South West 0
## 2189 2020-07-21 South West 0
## 2190 2020-07-22 South West 0
## 2191 2020-07-23 South West 0
## 2192 2020-07-24 South West 0
## 2193 2020-07-25 South West 0
## 2194 2020-07-26 South West 0
## 2195 2020-07-27 South West 0
## 2196 2020-07-28 South West 0
## 2197 2020-07-29 South West 0
## 2198 2020-07-30 South West 1
## 2199 2020-07-31 South West 0
## 2200 2020-08-01 South West 0
## 2201 2020-08-02 South West 0
## 2202 2020-08-03 South West 0
## 2203 2020-08-04 South West 0
## 2204 2020-08-05 South West 0
## 2205 2020-08-06 South West 0
## 2206 2020-08-07 South West 0
## 2207 2020-08-08 South West 0
## 2208 2020-08-09 South West 0
## 2209 2020-08-10 South West 0
## 2210 2020-08-11 South West 0
## 2211 2020-08-12 South West 0
## 2212 2020-08-13 South West 0
## 2213 2020-08-14 South West 1
## 2214 2020-08-15 South West 0
## 2215 2020-08-16 South West 0
## 2216 2020-08-17 South West 2
## 2217 2020-08-18 South West 0
## 2218 2020-08-19 South West 0
## 2219 2020-08-20 South West 0
## 2220 2020-08-21 South West 0
## 2221 2020-08-22 South West 0
## 2222 2020-08-23 South West 0
## 2223 2020-08-24 South West 0
## 2224 2020-08-25 South West 1
## 2225 2020-08-26 South West 0
## 2226 2020-08-27 South West 1
## 2227 2020-08-28 South West 0
## 2228 2020-08-29 South West 0
## 2229 2020-08-30 South West 0
## 2230 2020-08-31 South West 0
## 2231 2020-09-01 South West 0
## 2232 2020-09-02 South West 0
## 2233 2020-09-03 South West 0
## 2234 2020-09-04 South West 0
## 2235 2020-09-05 South West 0
## 2236 2020-09-06 South West 0
## 2237 2020-09-07 South West 0
## 2238 2020-09-08 South West 1
## 2239 2020-09-09 South West 0
## 2240 2020-09-10 South West 0
## 2241 2020-09-11 South West 0
## 2242 2020-09-12 South West 0
## 2243 2020-09-13 South West 1
## 2244 2020-09-14 South West 0
## 2245 2020-09-15 South West 0
## 2246 2020-09-16 South West 0
## 2247 2020-09-17 South West 1
## 2248 2020-09-18 South West 0
## 2249 2020-09-19 South West 0
## 2250 2020-09-20 South West 1
## 2251 2020-09-21 South West 0
## 2252 2020-09-22 South West 0
## 2253 2020-09-23 South West 0
## 2254 2020-09-24 South West 1
## 2255 2020-09-25 South West 0
## 2256 2020-09-26 South West 0
## 2257 2020-09-27 South West 0
## 2258 2020-09-28 South West 0
## 2259 2020-09-29 South West 0
## 2260 2020-09-30 South West 0
## 2261 2020-10-01 South West 0
## 2262 2020-10-02 South West 1
## 2263 2020-10-03 South West 0
## 2264 2020-10-04 South West 0
## 2265 2020-10-05 South West 0
## 2266 2020-10-06 South West 1
## 2267 2020-10-07 South West 0
## 2268 2020-10-08 South West 1
## 2269 2020-10-09 South West 1
## 2270 2020-10-10 South West 0
## 2271 2020-10-11 South West 4
## 2272 2020-10-12 South West 2
## 2273 2020-10-13 South West 0
## 2274 2020-10-14 South West 3
## 2275 2020-10-15 South West 1
## 2276 2020-10-16 South West 2
## 2277 2020-10-17 South West 8
## 2278 2020-10-18 South West 2
## 2279 2020-10-19 South West 2
## 2280 2020-10-20 South West 3
## 2281 2020-10-21 South West 6
## 2282 2020-10-22 South West 6
## 2283 2020-10-23 South West 5
## 2284 2020-10-24 South West 5
## 2285 2020-10-25 South West 5
## 2286 2020-10-26 South West 7
## 2287 2020-10-27 South West 6
## 2288 2020-10-28 South West 8
## 2289 2020-10-29 South West 11
## 2290 2020-10-30 South West 8
## 2291 2020-10-31 South West 4
## 2292 2020-11-01 South West 5
## 2293 2020-11-02 South West 11
## 2294 2020-11-03 South West 7
## 2295 2020-11-04 South West 8
## 2296 2020-11-05 South West 5
## 2297 2020-11-06 South West 11
## 2298 2020-11-07 South West 10
## 2299 2020-11-08 South West 10
## 2300 2020-11-09 South West 12
## 2301 2020-11-10 South West 6
## 2302 2020-11-11 South West 13
## 2303 2020-11-12 South West 17
## 2304 2020-11-13 South West 9
## 2305 2020-11-14 South West 8
## 2306 2020-11-15 South West 16
## 2307 2020-11-16 South West 18
## 2308 2020-11-17 South West 17
## 2309 2020-11-18 South West 26
## 2310 2020-11-19 South West 15
## 2311 2020-11-20 South West 25
## 2312 2020-11-21 South West 25
## 2313 2020-11-22 South West 24
## 2314 2020-11-23 South West 14
## 2315 2020-11-24 South West 20
## 2316 2020-11-25 South West 25
## 2317 2020-11-26 South West 16
## 2318 2020-11-27 South West 21
## 2319 2020-11-28 South West 35
## 2320 2020-11-29 South West 15
## 2321 2020-11-30 South West 21
## 2322 2020-12-01 South West 19
## 2323 2020-12-02 South West 15
## 2324 2020-12-03 South West 14
## 2325 2020-12-04 South West 20
## 2326 2020-12-05 South West 17
## 2327 2020-12-06 South West 13
## 2328 2020-12-07 South West 15
## 2329 2020-12-08 South West 19
## 2330 2020-12-09 South West 21
## 2331 2020-12-10 South West 20
## 2332 2020-12-11 South West 20
## 2333 2020-12-12 South West 15
## 2334 2020-12-13 South West 19
## 2335 2020-12-14 South West 20
## 2336 2020-12-15 South West 20
## 2337 2020-12-16 South West 9
## 2338 2020-12-17 South West 26
## 2339 2020-12-18 South West 11
## 2340 2020-12-19 South West 22
## 2341 2020-12-20 South West 19
## 2342 2020-12-21 South West 21
## 2343 2020-12-22 South West 10
## 2344 2020-12-23 South West 16
## 2345 2020-12-24 South West 18
## 2346 2020-12-25 South West 19
## 2347 2020-12-26 South West 24
## 2348 2020-12-27 South West 24
## 2349 2020-12-28 South West 20
## 2350 2020-12-29 South West 20
## 2351 2020-12-30 South West 14
## 2352 2020-12-31 South West 26
## 2353 2021-01-01 South West 28
## 2354 2021-01-02 South West 22
## 2355 2021-01-03 South West 24
## 2356 2021-01-04 South West 30
## 2357 2021-01-05 South West 31
## 2358 2021-01-06 South West 24
## 2359 2021-01-07 South West 29
## 2360 2021-01-08 South West 33
## 2361 2021-01-09 South West 26
## 2362 2021-01-10 South West 31
## 2363 2021-01-11 South West 36
## 2364 2021-01-12 South West 48
## 2365 2021-01-13 South West 40
## 2366 2021-01-14 South West 32
## 2367 2021-01-15 South West 44
## 2368 2021-01-16 South West 54
## 2369 2021-01-17 South West 32
## 2370 2021-01-18 South West 42
## 2371 2021-01-19 South West 43
## 2372 2021-01-20 South West 62
## 2373 2021-01-21 South West 54
## 2374 2021-01-22 South West 57
## 2375 2021-01-23 South West 52
## 2376 2021-01-24 South West 59
## 2377 2021-01-25 South West 55
## 2378 2021-01-26 South West 41
## 2379 2021-01-27 South West 39
## 2380 2021-01-28 South West 48
## 2381 2021-01-29 South West 41
## 2382 2021-01-30 South West 35
## 2383 2021-01-31 South West 32
## 2384 2021-02-01 South West 27
## 2385 2021-02-02 South West 31
## 2386 2021-02-03 South West 23
## 2387 2021-02-04 South West 21.5 Completion date
We extract the completion date from the NHS Pathways file timestamp:
The completion date of the NHS Pathways data is Thursday 04 Feb 2021.
1.6 Auxiliary functions
These are functions which will be used further in the analyses.
Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:
## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here
Rsq <- function(x) {
1 - (x$deviance / x$null.deviance)
}Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:
## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals
get_r <- function(model) {
## extract coefficients and conf int
out <- data.frame(r = coef(model)) %>%
rownames_to_column("var") %>%
cbind(confint(model)) %>%
filter(!grepl("day_of_week", var)) %>%
filter(grepl("day", var)) %>%
rename(lower_95 = "2.5 %",
upper_95 = "97.5 %") %>%
mutate(var = sub("day:", "", var))
## reconstruct values: intercept + region-coefficient
for (i in 2:nrow(out)) {
out[i, -1] <- out[1, -1] + out[i, -1]
}
## find the name of the intercept, restore regions names
out <- out %>%
mutate(nhs_region = model$xlevels$nhs_region) %>%
select(nhs_region, everything(), -var)
## find halving times
halving <- log(0.5) / out[,-1] %>%
rename(halving_t = r,
halving_t_lower_95 = lower_95,
halving_t_upper_95 = upper_95)
## set halving times with exclusion intervals to NA
no_halving <- out$lower_95 < 0 & out$upper_95 > 0
halving[no_halving, ] <- NA_real_
## return all data
cbind(out, halving)
}Functions used in the correlation analysis between NHS Pathways reports and deaths:
## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.
getcor <- function(x, ndx) {
return(cor(x$deaths[ndx],
x$note_lag[ndx],
use = "complete.obs",
method = "pearson"))
}
## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)
getboot <- function(x) {
result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000),
type = "bca")
return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
r = result$t0,
r_low = result$bca[4],
r_hi = result$bca[5]))
}Function to classify the day of the week into weekend, Monday, and the rest:
## Fn to add day of week
day_of_week <- function(df) {
df %>%
dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>%
dplyr::mutate(day_of_week = dplyr::case_when(
day_of_week %in% c("Sat", "Sun") ~ "weekend",
day_of_week %in% c("Mon") ~ "monday",
!(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
) %>%
factor(levels = c("rest_of_week", "monday", "weekend")))
}Custom color palettes, color scales, and vectors of colors:
2 Temporal trends in NHS Pathways reports
2.1 Outline
We look for temporal patterns in COVID-19 related 111/999 calls and 111 online reports. Analyses are broken down by NHS region. We also look for estimates of recent growth rate and associated doubling / halving time.
2.2 Reports by region over time
tab_date_region_all <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
dth %>%
mutate(trusted = case_when(date_report < max(dth$date_report)-delay_max ~ "Y",
date_report >= max(dth$date_report)-delay_max ~ "N"),
value = "Deaths",
vline = max(dth$date_report)-delay_max-1,
lab = "Truncated for reporting delay",
lab_pos_x = vline + 10,
lab_pos_y = 150,
lab_col = "darkgrey") %>%
rename(date = date_report,
n = deaths) %>%
bind_rows(
mutate(tab_date_region_all, value = "Reports",
trusted = "Y",
vline = as.Date("2020-03-23"),
lab = "Start of UK lockdown",
lab_pos_x = vline - 8,
lab_pos_y = 30200,
lab_col = "black")
) %>%
mutate(value = factor(value, levels = c("Reports","Deaths"))) -> dths_reports
plot_dth_report <-
ggplot(dths_reports, aes(date, n, colour = nhs_region)) +
# Add main points and lines, coloured by region and fade out deaths for excluded period
geom_point(aes(alpha = trusted)) +
geom_line(alpha = 0.2) +
geom_smooth(method = "loess", span = .5, color = "black") +
scale_colour_manual("", values = pal) +
scale_alpha_manual(values = c(0.3,1)) +
guides(alpha = F) +
# Add vertical markers for important dates with labels - different for each facet
ggnewscale::new_scale_colour() +
geom_vline(aes(xintercept = vline, col = value), lty = "solid") +
geom_text(aes(x = lab_pos_x, y = lab_pos_y, label = lab, col = value), size = 3) +
scale_colour_manual("",values = c("black","darkgrey"), guide = F) +
# Facet by deaths and reports
facet_grid(rows = vars(value), scales = "free_y", switch = "y") +
# Other formatting
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",strip.placement = "outside") +
rotate_x +
labs(x = NULL,
y = NULL)
plot_dth_report
2.3 Reports by region by age over time
We plot the number of 111/999 calls and 111 online reports by age, and the proportion of 111/999 calls and 111 online reports by age. In the second graph, the vertical lines indicate the proportion of individuals residing in the corresponding NHS region who belong to the corresponding age group.
tab_date_region_age_all <- x %>%
filter(!is.na(nhs_region),
age != "missing") %>%
group_by(date, nhs_region, age) %>%
summarise(n = sum(count))
tab_date_region_age_all %>%
ggplot(aes(x = date, y = n, fill = age)) +
geom_col(position = "stack") +
scale_fill_manual(values = age.pal) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(fill = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Total daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
tab_date_region_age_all <- tab_date_region_age_all %>%
group_by(date, nhs_region) %>%
summarise(tot = sum(n)) %>%
left_join(tab_date_region_age_all, by = c("date", "nhs_region")) %>%
mutate(prop_n = n/tot)
tab_date_region_age_all %>%
ggplot(aes(x = date, y = prop_n, color = age)) +
scale_color_manual(values = age.pal) +
geom_line() +
geom_point() +
geom_hline(data = nhs_region_pop, aes(yintercept = value, color = variable)) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(color = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Proportion of daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
2.4 Moving window model
We fit quasi-Poisson GLMs for 14-day windows to get growth rates over time.
## set moving time window (1/2/3 weeks)
w <- 14
# create empty df
r_all_sliding <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding <- bind_rows(r_all_sliding, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding <- r_all_sliding %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))We examine the evolution of the growth rate by region over time.
# plot
plot_growth <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)From the growth rate, we derive R and examine its value through time.
# plot
plot_R <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
rotate_x +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
# strip.text.x = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "",
override.aes = list(fill = NA)),
fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))
2.5 Moving window model - stratified by age
We repeat the above analysis, where we fit quasi-Poisson GLMs for 14-day windows to get growth rates over time, but apply this to each age group separately (0-18, 19-69, 70-120 years old).
We first run the analysis for 0-18 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_0_18 <- NULL
## make data for model
x_model_all_moving_0_18 <- x %>%
filter(!is.na(nhs_region),
age == "0-18") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_0_18$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_0_18 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_0_18 <- bind_rows(r_all_sliding_0_18, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_0_18 <- r_all_sliding_0_18 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_0_18 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_0_18 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_0_18 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then, we run the analysis for 19-69 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_19_69 <- NULL
## make data for model
x_model_all_moving_19_69 <- x %>%
filter(!is.na(nhs_region),
age == "19-69") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_19_69$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_19_69 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_19_69 <- bind_rows(r_all_sliding_19_69, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_19_69 <- r_all_sliding_19_69 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_19_69 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_19_69 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_19_69 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Finally, we run the analysis for 70-120 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_70_120 <- NULL
## make data for model
x_model_all_moving_70_120 <- x %>%
filter(!is.na(nhs_region),
age == "70-120") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_70_120$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_70_120 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_70_120 <- bind_rows(r_all_sliding_70_120, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_70_120 <- r_all_sliding_70_120 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_70_120 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_70_120 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_70_120 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)"))) We combine the estimated growth rates and effective reproduction numbers into a single figure.
ggpubr::ggarrange(fig2_3_0_18,
fig2_3_19_69,
fig2_3_70_120,
nrow = 3,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom",
align = "hv") 
3 Comparison with deaths time series
3.1 Outline
We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.
Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.
3.2 Lagged correlation
We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.
First we join the NHS Pathways and death data, and aggregate over all England:
## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max
dth_trunc <- dth %>%
rename(date = date_report) %>%
filter(date <= trunc_date)
## join with notification data
all_data <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(count = sum(count, na.rm = T)) %>%
ungroup %>%
inner_join(dth_trunc,
by = c("date","nhs_region"))
all_tot <- all_data %>%
group_by(date) %>%
summarise(count = sum(count, na.rm = TRUE),
deaths = sum(deaths, na.rm = TRUE)) We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:
## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
## lag reports
summary <- all_tot %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI
getboot(.) %>%
mutate(lag = i)
lag_cor <- bind_rows(lag_cor, summary)
}
cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
theme_bw() +
geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_point() +
geom_line() +
labs(x = "Lag between NHS pathways and death data (days)",
y = "Pearson's correlation") +
large_txt
cor_vs_lag
This analysis suggests that the best lag is 16 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 16 days.
all_tot <- all_tot %>%
rename(date_death = date) %>%
mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
date_note = lag(date_death,16))
lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")
summary(lag_mod)
##
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -16.463 -13.829 -4.620 8.092 35.105
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.930e+00 6.975e-02 70.68 <2e-16 ***
## note_lag 1.358e-05 1.141e-06 11.91 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 172.9335)
##
## Null deviance: 63681 on 286 degrees of freedom
## Residual deviance: 45997 on 285 degrees of freedom
## (16 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 5
exp(coefficients(lag_mod))
## (Intercept) note_lag
## 138.352090 1.000014
exp(confint(lag_mod))
## 2.5 % 97.5 %
## (Intercept) 120.349978 158.209941
## note_lag 1.000011 1.000016
Rsq(lag_mod)
## [1] 0.2776966
mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])
all_tot_pred <-
all_tot %>%
filter(!is.na(note_lag)) %>%
mutate(pred = mod_fit$fit,
pred.se = mod_fit$se.fit,
low = exp(pred - 1.96*pred.se),
hi = exp(pred + 1.96*pred.se))
glm_fit <- all_tot_pred %>%
filter(!is.na(note_lag)) %>%
ggplot(aes(x = note_lag, y = deaths)) +
geom_point() +
geom_line(aes(y = exp(pred))) +
geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
theme_bw() +
labs(y = "Daily number of\ndeaths reported",
x = "Daily number of NHS Pathways reports") +
large_txt
glm_fit
4 Supplementary figures
4.1 Serial interval distribution
This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.
SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
meanlog = log(4.7),
sdlog = log(2.9), w = 0.5)
SI_dist1 <- data.frame(x = SI_distribution$r(1e5))
SI_dist1 <- count(SI_dist1, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 30, 5)) +
theme_bw()
SI_dist2 <- data.frame(x = SI_distribution2$r(1e5))
SI_dist2 <- count(SI_dist2, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
theme_bw()
ggpubr::ggarrange(SI_dist1,
SI_dist2,
nrow = 1,
labels = "AUTO") 
4.2 Sensitivity analysis - 7 or 21 days moving window
We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.
First with the 7 days window:
## set moving time window (1/2/3 weeks)
w <- 7
# create empty df
r_all_sliding_7days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)plot_R <- r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_7days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_7days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_7 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then with the 21 days window:
## set moving time window (1/2/3 weeks)
w <- 21
# create empty df
r_all_sliding_21days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_21days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_21days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_21 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))And we combine both outputs into a single plot:
ggpubr::ggarrange(r_R_7,
r_R_21,
nrow = 2,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom") 
4.3 Correlation between NHS Pathways reports and deaths by NHS region
lag_cor_reg <- data.frame()
for (i in 0:30) {
summary <-
all_data %>%
group_by(nhs_region) %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI for each region
group_modify(~getboot(.x)) %>%
mutate(lag = i)
lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}
cor_vs_lag_reg <-
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
geom_point() +
geom_line() +
facet_wrap(~nhs_region) +
scale_color_manual(values = pal) +
scale_fill_manual(values = pal, guide = F) +
theme_bw() +
labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
theme(legend.position = "bottom") +
guides(color = guide_legend(override.aes = list(fill = NA)))
cor_vs_lag_reg
5 Export data
We save the tables created during our analysis:
if (!dir.exists("excel_tables")) {
dir.create("excel_tables")
}
## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")
for (e in tables_to_export) {
rio::export(get(e),
file.path("excel_tables",
paste0(e, ".xlsx")))
}
## also export result from regression on lagged data
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))6 System information
6.1 Outline
The following information documents the system on which the document was compiled.
6.2 System
This provides information on the operating system.
Sys.info()
## sysname
## "Darwin"
## release
## "19.6.0"
## version
## "Darwin Kernel Version 19.6.0: Tue Nov 10 00:10:30 PST 2020; root:xnu-6153.141.10~1/RELEASE_X86_64"
## nodename
## "Mac-1612605896605.local"
## machine
## "x86_64"
## login
## "root"
## user
## "runner"
## effective_user
## "runner"6.3 R environment
This provides information on the version of R used:
6.4 R packages
This provides information on the packages used:
sessionInfo()
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggnewscale_0.4.5 ggpubr_0.4.0 lubridate_1.7.9.2
## [4] chngpt_2020.10-12 cyphr_1.1.0 DT_0.17
## [7] kableExtra_1.3.1 janitor_2.1.0 remotes_2.2.0
## [10] projections_0.5.2 earlyR_0.0.5 epitrix_0.2.2
## [13] distcrete_1.0.3 incidence_1.7.3 rio_0.5.16
## [16] reshape2_1.4.4 rvest_0.3.6 xml2_1.3.2
## [19] linelist_0.0.40.9000 forcats_0.5.1 stringr_1.4.0
## [22] dplyr_1.0.4 purrr_0.3.4 readr_1.4.0
## [25] tidyr_1.1.2 tibble_3.0.6 ggplot2_3.3.3
## [28] tidyverse_1.3.0 here_1.0.1 reportfactory_0.0.5
##
## loaded via a namespace (and not attached):
## [1] minqa_1.2.4 colorspace_2.0-0 selectr_0.4-2 ggsignif_0.6.0
## [5] ellipsis_0.3.1 rprojroot_2.0.2 snakecase_0.11.0 fs_1.5.0
## [9] rstudioapi_0.13 farver_2.0.3 fansi_0.4.2 splines_4.0.3
## [13] knitr_1.31 jsonlite_1.7.2 nloptr_1.2.2.2 broom_0.7.4
## [17] dbplyr_2.1.0 compiler_4.0.3 httr_1.4.2 backports_1.2.1
## [21] assertthat_0.2.1 Matrix_1.2-18 cli_2.3.0 htmltools_0.5.1.1
## [25] tools_4.0.3 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.6
## [29] carData_3.0-4 cellranger_1.1.0 vctrs_0.3.6 nlme_3.1-149
## [33] matchmaker_0.1.1 crosstalk_1.1.1 xfun_0.20 ps_1.5.0
## [37] openxlsx_4.2.3 lme4_1.1-26 lifecycle_0.2.0 statmod_1.4.35
## [41] rstatix_0.6.0 MASS_7.3-53 scales_1.1.1 hms_1.0.0
## [45] parallel_4.0.3 sodium_1.1 yaml_2.2.1 curl_4.3
## [49] gridExtra_2.3 stringi_1.5.3 highr_0.8 kyotil_2020.10-12
## [53] boot_1.3-25 zip_2.1.1 rlang_0.4.10 pkgconfig_2.0.3
## [57] evaluate_0.14 lattice_0.20-41 labeling_0.4.2 htmlwidgets_1.5.3
## [61] cowplot_1.1.1 tidyselect_1.1.0 plyr_1.8.6 magrittr_2.0.1
## [65] R6_2.5.0 generics_0.1.0 DBI_1.1.1 pillar_1.4.7
## [69] haven_2.3.1 foreign_0.8-80 withr_2.4.1 mgcv_1.8-33
## [73] survival_3.2-7 abind_1.4-5 modelr_0.1.8 crayon_1.4.0
## [77] car_3.0-10 utf8_1.1.4 rmarkdown_2.6 viridis_0.5.1
## [81] grid_4.0.3 readxl_1.3.1 data.table_1.13.6 reprex_1.0.0
## [85] digest_0.6.27 webshot_0.5.2 munsell_0.5.0 viridisLite_0.3.0